id	sid	tid	token	lemma	pos
bracis-19081	1	1	deep	deep	ADJ
bracis-19081	1	2	active	active	ADJ
bracis-19081	1	3	-	-	PUNCT
bracis-19081	1	4	self	self	NOUN
bracis-19081	1	5	learning	learning	NOUN
bracis-19081	1	6	applied	apply	VERB
bracis-19081	1	7	to	to	ADP
bracis-19081	1	8	named	name	VERB
bracis-19081	1	9	entity	entity	NOUN
bracis-19081	1	10	recognition	recognition	NOUN
bracis-19081	1	11	|	|	NOUN
bracis-19081	1	12	springer	springer	NOUN
bracis-19081	1	13	nature	nature	PROPN
bracis-19081	1	14	link	link	PROPN
bracis-19081	1	15	(	(	PUNCT
bracis-19081	1	16	formerly	formerly	ADV
bracis-19081	1	17	springerlink	springerlink	NOUN
bracis-19081	1	18	)	)	PUNCT
bracis-19081	1	19	skip	skip	VERB
bracis-19081	1	20	to	to	ADP
bracis-19081	1	21	main	main	ADJ
bracis-19081	1	22	content	content	NOUN
bracis-19081	1	23	advertisement	advertisement	NOUN
bracis-19081	1	24	log	log	NOUN
bracis-19081	1	25	in	in	ADP
bracis-19081	1	26	menu	menu	NOUN
bracis-19081	1	27	find	find	VERB
bracis-19081	1	28	a	a	DET
bracis-19081	1	29	journal	journal	NOUN
bracis-19081	1	30	publish	publish	VERB
bracis-19081	1	31	with	with	ADP
bracis-19081	1	32	us	we	PRON
bracis-19081	1	33	track	track	VERB
bracis-19081	1	34	your	your	PRON
bracis-19081	1	35	research	research	NOUN
bracis-19081	1	36	search	search	NOUN
bracis-19081	1	37	cart	cart	NOUN
bracis-19081	1	38	home	home	NOUN
bracis-19081	1	39	intelligent	intelligent	ADJ
bracis-19081	1	40	systems	system	NOUN
bracis-19081	1	41	conference	conference	NOUN
bracis-19081	1	42	paper	paper	NOUN
bracis-19081	1	43	deep	deep	ADV
bracis-19081	1	44	active	active	ADJ
bracis-19081	1	45	-	-	PUNCT
bracis-19081	1	46	self	self	NOUN
bracis-19081	1	47	learning	learning	NOUN
bracis-19081	1	48	applied	apply	VERB
bracis-19081	1	49	to	to	ADP
bracis-19081	1	50	named	name	VERB
bracis-19081	1	51	entity	entity	NOUN
bracis-19081	1	52	recognition	recognition	NOUN
bracis-19081	1	53	conference	conference	NOUN
bracis-19081	1	54	paper	paper	NOUN
bracis-19081	1	55	first	first	ADV
bracis-19081	1	56	online	online	ADV
bracis-19081	1	57	:	:	PUNCT
bracis-19081	1	58	28	28	NUM
bracis-19081	1	59	november	november	PROPN
bracis-19081	1	60	2021	2021	NUM
bracis-19081	2	1	pp	pp	ADP
bracis-19081	2	2	405–418	405–418	NUM
bracis-19081	2	3	cite	cite	VERB
bracis-19081	2	4	this	this	DET
bracis-19081	2	5	conference	conference	NOUN
bracis-19081	2	6	paper	paper	NOUN
bracis-19081	2	7	access	access	NOUN
bracis-19081	2	8	provided	provide	VERB
bracis-19081	2	9	by	by	ADP
bracis-19081	2	10	university	university	PROPN
bracis-19081	2	11	of	of	ADP
bracis-19081	2	12	notre	notre	PROPN
bracis-19081	2	13	dame	dame	PROPN
bracis-19081	2	14	hesburgh	hesburgh	PROPN
bracis-19081	2	15	library	library	PROPN
bracis-19081	2	16	download	download	PROPN
bracis-19081	2	17	book	book	NOUN
bracis-19081	2	18	pdf	pdf	PROPN
bracis-19081	2	19	download	download	NOUN
bracis-19081	2	20	book	book	NOUN
bracis-19081	2	21	epub	epub	PROPN
bracis-19081	2	22	intelligent	intelligent	ADJ
bracis-19081	2	23	systems	system	NOUN
bracis-19081	2	24	(	(	PUNCT
bracis-19081	2	25	bracis	bracis	NOUN
bracis-19081	2	26	2021	2021	NUM
bracis-19081	2	27	)	)	PUNCT
bracis-19081	2	28	deep	deep	ADJ
bracis-19081	2	29	active	active	ADJ
bracis-19081	2	30	-	-	PUNCT
bracis-19081	2	31	self	self	NOUN
bracis-19081	2	32	learning	learning	NOUN
bracis-19081	2	33	applied	apply	VERB
bracis-19081	2	34	to	to	ADP
bracis-19081	2	35	named	name	VERB
bracis-19081	2	36	entity	entity	NOUN
bracis-19081	2	37	recognition	recognition	NOUN
bracis-19081	2	38	download	download	NOUN
bracis-19081	2	39	book	book	NOUN
bracis-19081	2	40	pdf	pdf	PROPN
bracis-19081	2	41	download	download	NOUN
bracis-19081	2	42	book	book	PROPN
bracis-19081	2	43	epub	epub	PROPN
bracis-19081	2	44	josé	josé	PROPN
bracis-19081	2	45	reinaldo	reinaldo	PROPN
bracis-19081	3	1	c.	c.	PROPN
bracis-19081	3	2	s.	s.	PROPN
bracis-19081	3	3	a.	a.	PROPN
bracis-19081	3	4	v.	v.	PROPN
bracis-19081	3	5	s.	s.	PROPN
bracis-19081	3	6	neto10	neto10	PROPN
bracis-19081	3	7	&	&	CCONJ
bracis-19081	3	8	thiago	thiago	PROPN
bracis-19081	3	9	de	de	PROPN
bracis-19081	3	10	paulo	paulo	PROPN
bracis-19081	3	11	faleiros10	faleiros10	NOUN
bracis-19081	3	12	  	  	SPACE
bracis-19081	3	13	part	part	NOUN
bracis-19081	3	14	of	of	ADP
bracis-19081	3	15	the	the	DET
bracis-19081	3	16	book	book	NOUN
bracis-19081	3	17	series	series	NOUN
bracis-19081	3	18	:	:	PUNCT
bracis-19081	3	19	lecture	lecture	NOUN
bracis-19081	3	20	notes	note	NOUN
bracis-19081	3	21	in	in	ADP
bracis-19081	3	22	computer	computer	NOUN
bracis-19081	3	23	science	science	NOUN
bracis-19081	3	24	(	(	PUNCT
bracis-19081	3	25	(	(	PUNCT
bracis-19081	3	26	lnai	lnai	ADJ
bracis-19081	3	27	,	,	PUNCT
bracis-19081	3	28	volume	volume	NOUN
bracis-19081	3	29	13074	13074	NUM
bracis-19081	3	30	)	)	PUNCT
bracis-19081	3	31	)	)	PUNCT
bracis-19081	3	32	included	include	VERB
bracis-19081	3	33	in	in	ADP
bracis-19081	3	34	the	the	DET
bracis-19081	3	35	following	follow	VERB
bracis-19081	3	36	conference	conference	NOUN
bracis-19081	3	37	series	series	NOUN
bracis-19081	3	38	:	:	PUNCT
bracis-19081	3	39	brazilian	brazilian	ADJ
bracis-19081	3	40	conference	conference	NOUN
bracis-19081	3	41	on	on	ADP
bracis-19081	3	42	intelligent	intelligent	ADJ
bracis-19081	3	43	systems	system	NOUN
bracis-19081	3	44	1274	1274	NUM
bracis-19081	3	45	accesses	access	VERB
bracis-19081	3	46	4	4	NUM
bracis-19081	3	47	citations	citation	NOUN
bracis-19081	3	48	abstract	abstract	ADJ
bracis-19081	3	49	deep	deep	ADJ
bracis-19081	3	50	learning	learning	NOUN
bracis-19081	3	51	models	model	NOUN
bracis-19081	3	52	have	have	AUX
bracis-19081	3	53	been	be	AUX
bracis-19081	3	54	the	the	DET
bracis-19081	3	55	state	state	NOUN
bracis-19081	3	56	-	-	PUNCT
bracis-19081	3	57	of	of	ADP
bracis-19081	3	58	-	-	PUNCT
bracis-19081	3	59	the	the	DET
bracis-19081	3	60	-	-	PUNCT
bracis-19081	3	61	art	art	NOUN
bracis-19081	3	62	for	for	ADP
bracis-19081	3	63	a	a	DET
bracis-19081	3	64	variety	variety	NOUN
bracis-19081	3	65	of	of	ADP
bracis-19081	3	66	challenging	challenging	ADJ
bracis-19081	3	67	tasks	task	NOUN
bracis-19081	3	68	in	in	ADP
bracis-19081	3	69	natural	natural	ADJ
bracis-19081	3	70	language	language	NOUN
bracis-19081	3	71	processing	processing	NOUN
bracis-19081	3	72	,	,	PUNCT
bracis-19081	3	73	but	but	CCONJ
bracis-19081	3	74	to	to	PART
bracis-19081	3	75	achieve	achieve	VERB
bracis-19081	3	76	good	good	ADJ
bracis-19081	3	77	results	result	NOUN
bracis-19081	3	78	they	they	PRON
bracis-19081	3	79	often	often	ADV
bracis-19081	3	80	require	require	VERB
bracis-19081	3	81	big	big	ADJ
bracis-19081	3	82	labeled	label	VERB
bracis-19081	3	83	datasets	dataset	NOUN
bracis-19081	3	84	.	.	PUNCT
bracis-19081	4	1	deep	deep	ADJ
bracis-19081	4	2	active	active	ADJ
bracis-19081	4	3	learning	learn	VERB
bracis-19081	4	4	algorithms	algorithm	NOUN
bracis-19081	4	5	were	be	AUX
bracis-19081	4	6	designed	design	VERB
bracis-19081	4	7	to	to	PART
bracis-19081	4	8	reduce	reduce	VERB
bracis-19081	4	9	the	the	DET
bracis-19081	4	10	annotation	annotation	NOUN
bracis-19081	4	11	cost	cost	NOUN
bracis-19081	4	12	for	for	ADP
bracis-19081	4	13	training	train	VERB
bracis-19081	4	14	such	such	ADJ
bracis-19081	4	15	models	model	NOUN
bracis-19081	4	16	.	.	PUNCT
bracis-19081	5	1	current	current	ADJ
bracis-19081	5	2	deep	deep	ADJ
bracis-19081	5	3	active	active	ADJ
bracis-19081	5	4	learning	learning	NOUN
bracis-19081	5	5	algorithms	algorithm	NOUN
bracis-19081	5	6	,	,	PUNCT
bracis-19081	5	7	however	however	ADV
bracis-19081	5	8	,	,	PUNCT
bracis-19081	5	9	aim	aim	VERB
bracis-19081	5	10	at	at	ADP
bracis-19081	5	11	training	train	VERB
bracis-19081	5	12	a	a	DET
bracis-19081	5	13	good	good	ADJ
bracis-19081	5	14	deep	deep	ADJ
bracis-19081	5	15	learning	learning	NOUN
bracis-19081	5	16	model	model	NOUN
bracis-19081	5	17	with	with	ADP
bracis-19081	5	18	as	as	ADV
bracis-19081	5	19	little	little	ADJ
bracis-19081	5	20	labeled	label	VERB
bracis-19081	5	21	data	datum	NOUN
bracis-19081	5	22	as	as	ADP
bracis-19081	5	23	possible	possible	ADJ
bracis-19081	5	24	,	,	PUNCT
bracis-19081	5	25	and	and	CCONJ
bracis-19081	5	26	as	as	ADP
bracis-19081	5	27	such	such	ADJ
bracis-19081	5	28	are	be	AUX
bracis-19081	5	29	not	not	PART
bracis-19081	5	30	useful	useful	ADJ
bracis-19081	5	31	in	in	ADP
bracis-19081	5	32	scenarios	scenario	NOUN
bracis-19081	5	33	where	where	SCONJ
bracis-19081	5	34	the	the	DET
bracis-19081	5	35	full	full	ADJ
bracis-19081	5	36	dataset	dataset	NOUN
bracis-19081	5	37	must	must	AUX
bracis-19081	5	38	be	be	AUX
bracis-19081	5	39	labeled	label	VERB
bracis-19081	5	40	.	.	PUNCT
bracis-19081	6	1	as	as	ADP
bracis-19081	6	2	a	a	DET
bracis-19081	6	3	solution	solution	NOUN
bracis-19081	6	4	to	to	ADP
bracis-19081	6	5	this	this	DET
bracis-19081	6	6	problem	problem	NOUN
bracis-19081	6	7	,	,	PUNCT
bracis-19081	6	8	this	this	DET
bracis-19081	6	9	work	work	NOUN
bracis-19081	6	10	investigates	investigate	VERB
bracis-19081	6	11	deep	deep	ADJ
bracis-19081	6	12	active	active	ADJ
bracis-19081	6	13	-	-	PUNCT
bracis-19081	6	14	self	self	NOUN
bracis-19081	6	15	learning	learn	VERB
bracis-19081	6	16	algorithms	algorithm	NOUN
bracis-19081	6	17	that	that	PRON
bracis-19081	6	18	employ	employ	VERB
bracis-19081	6	19	self	self	NOUN
bracis-19081	6	20	-	-	PUNCT
bracis-19081	6	21	labeling	labeling	NOUN
bracis-19081	6	22	using	use	VERB
bracis-19081	6	23	the	the	DET
bracis-19081	6	24	trained	train	VERB
bracis-19081	6	25	model	model	NOUN
bracis-19081	6	26	to	to	PART
bracis-19081	6	27	help	help	VERB
bracis-19081	6	28	alleviate	alleviate	VERB
bracis-19081	6	29	the	the	DET
bracis-19081	6	30	cost	cost	NOUN
bracis-19081	6	31	of	of	ADP
bracis-19081	6	32	annotating	annotate	VERB
bracis-19081	6	33	full	full	ADJ
bracis-19081	6	34	datasets	dataset	NOUN
bracis-19081	6	35	for	for	ADP
bracis-19081	6	36	named	name	VERB
bracis-19081	6	37	entity	entity	NOUN
bracis-19081	6	38	recognition	recognition	NOUN
bracis-19081	6	39	tasks	task	NOUN
bracis-19081	6	40	.	.	PUNCT
bracis-19081	7	1	the	the	DET
bracis-19081	7	2	experiments	experiment	NOUN
bracis-19081	7	3	performed	perform	VERB
bracis-19081	7	4	indicate	indicate	VERB
bracis-19081	7	5	that	that	SCONJ
bracis-19081	7	6	the	the	DET
bracis-19081	7	7	proposed	propose	VERB
bracis-19081	7	8	deep	deep	ADJ
bracis-19081	7	9	active	active	ADJ
bracis-19081	7	10	-	-	PUNCT
bracis-19081	7	11	self	self	NOUN
bracis-19081	7	12	learning	learn	VERB
bracis-19081	7	13	algorithm	algorithm	NOUN
bracis-19081	7	14	is	be	AUX
bracis-19081	7	15	capable	capable	ADJ
bracis-19081	7	16	of	of	ADP
bracis-19081	7	17	reducing	reduce	VERB
bracis-19081	7	18	manual	manual	ADJ
bracis-19081	7	19	annotation	annotation	NOUN
bracis-19081	7	20	costs	cost	NOUN
bracis-19081	7	21	for	for	ADP
bracis-19081	7	22	labeling	label	VERB
bracis-19081	7	23	the	the	DET
bracis-19081	7	24	complete	complete	ADJ
bracis-19081	7	25	dataset	dataset	NOUN
bracis-19081	7	26	for	for	ADP
bracis-19081	7	27	named	name	VERB
bracis-19081	7	28	entity	entity	NOUN
bracis-19081	7	29	recognition	recognition	NOUN
bracis-19081	7	30	with	with	ADP
bracis-19081	7	31	less	less	ADJ
bracis-19081	7	32	than	than	ADP
bracis-19081	7	33	2	2	NUM
bracis-19081	7	34	%	%	NOUN
bracis-19081	7	35	of	of	ADP
bracis-19081	7	36	the	the	DET
bracis-19081	7	37	self	self	NOUN
bracis-19081	7	38	labeled	label	VERB
bracis-19081	7	39	tokens	token	NOUN
bracis-19081	7	40	being	be	AUX
bracis-19081	7	41	mislabeled	mislabele	VERB
bracis-19081	7	42	.	.	PUNCT
bracis-19081	8	1	we	we	PRON
bracis-19081	8	2	also	also	ADV
bracis-19081	8	3	investigate	investigate	VERB
bracis-19081	8	4	an	an	DET
bracis-19081	8	5	early	early	ADJ
bracis-19081	8	6	stopping	stopping	NOUN
bracis-19081	8	7	technique	technique	NOUN
bracis-19081	8	8	that	that	PRON
bracis-19081	8	9	does	do	AUX
bracis-19081	8	10	n’t	not	PART
bracis-19081	8	11	rely	rely	VERB
bracis-19081	8	12	on	on	ADP
bracis-19081	8	13	a	a	DET
bracis-19081	8	14	validation	validation	NOUN
bracis-19081	8	15	set	set	NOUN
bracis-19081	8	16	,	,	PUNCT
bracis-19081	8	17	which	which	PRON
bracis-19081	8	18	effectively	effectively	ADV
bracis-19081	8	19	reduces	reduce	VERB
bracis-19081	8	20	even	even	ADV
bracis-19081	8	21	further	far	ADV
bracis-19081	8	22	the	the	DET
bracis-19081	8	23	annotation	annotation	NOUN
bracis-19081	8	24	costs	cost	NOUN
bracis-19081	8	25	of	of	ADP
bracis-19081	8	26	the	the	DET
bracis-19081	8	27	proposed	propose	VERB
bracis-19081	8	28	active	active	ADJ
bracis-19081	8	29	-	-	PUNCT
bracis-19081	8	30	self	self	NOUN
bracis-19081	8	31	learning	learn	VERB
bracis-19081	8	32	algorithm	algorithm	NOUN
bracis-19081	8	33	in	in	ADP
bracis-19081	8	34	real	real	ADJ
bracis-19081	8	35	world	world	NOUN
bracis-19081	8	36	scenarios	scenario	NOUN
bracis-19081	8	37	.	.	PUNCT
bracis-19081	9	1	access	access	NOUN
bracis-19081	9	2	provided	provide	VERB
bracis-19081	9	3	by	by	ADP
bracis-19081	9	4	university	university	PROPN
bracis-19081	9	5	of	of	ADP
bracis-19081	9	6	notre	notre	PROPN
bracis-19081	9	7	dame	dame	PROPN
bracis-19081	9	8	hesburgh	hesburgh	PROPN
bracis-19081	9	9	library	library	PROPN
bracis-19081	9	10	.	.	PUNCT
bracis-19081	10	1	download	download	PROPN
bracis-19081	10	2	conference	conference	NOUN
bracis-19081	10	3	paper	paper	NOUN
bracis-19081	10	4	pdf	pdf	NOUN
bracis-19081	10	5	similar	similar	ADJ
bracis-19081	10	6	content	content	NOUN
bracis-19081	10	7	being	be	AUX
bracis-19081	10	8	viewed	view	VERB
bracis-19081	10	9	by	by	ADP
bracis-19081	10	10	others	other	NOUN
bracis-19081	10	11	investigation	investigation	NOUN
bracis-19081	10	12	of	of	ADP
bracis-19081	10	13	 	 	SPACE
bracis-19081	10	14	deep	deep	ADJ
bracis-19081	10	15	active	active	ADJ
bracis-19081	10	16	self	self	NOUN
bracis-19081	10	17	-	-	PUNCT
bracis-19081	10	18	learning	learn	VERB
bracis-19081	10	19	algorithms	algorithm	NOUN
bracis-19081	10	20	applied	apply	VERB
bracis-19081	10	21	to	to	ADP
bracis-19081	10	22	 	 	SPACE
bracis-19081	10	23	named	name	VERB
bracis-19081	10	24	entity	entity	NOUN
bracis-19081	10	25	recognition	recognition	NOUN
bracis-19081	10	26	chapter	chapter	NOUN
bracis-19081	10	27	©	©	PROPN
bracis-19081	10	28	2023	2023	NUM
bracis-19081	10	29	a	a	DET
bracis-19081	10	30	framework	framework	NOUN
bracis-19081	10	31	of	of	ADP
bracis-19081	10	32	data	datum	NOUN
bracis-19081	10	33	augmentation	augmentation	NOUN
bracis-19081	10	34	while	while	SCONJ
bracis-19081	10	35	active	active	ADJ
bracis-19081	10	36	learning	learning	NOUN
bracis-19081	10	37	for	for	ADP
bracis-19081	10	38	chinese	chinese	ADJ
bracis-19081	10	39	named	name	VERB
bracis-19081	10	40	entity	entity	NOUN
bracis-19081	10	41	recognition	recognition	NOUN
bracis-19081	10	42	chapter	chapter	NOUN
bracis-19081	10	43	©	©	PROPN
bracis-19081	10	44	2021	2021	NUM
bracis-19081	10	45	deep	deep	ADJ
bracis-19081	10	46	entity	entity	NOUN
bracis-19081	10	47	matching	match	VERB
bracis-19081	10	48	with	with	ADP
bracis-19081	10	49	adversarial	adversarial	ADJ
bracis-19081	10	50	active	active	ADJ
bracis-19081	10	51	learning	learn	VERB
bracis-19081	10	52	article	article	NOUN
bracis-19081	10	53	28	28	NUM
bracis-19081	10	54	april	april	PROPN
bracis-19081	10	55	2022	2022	NUM
bracis-19081	10	56	explore	explore	VERB
bracis-19081	10	57	related	relate	VERB
bracis-19081	10	58	subjects	subject	NOUN
bracis-19081	10	59	discover	discover	VERB
bracis-19081	10	60	the	the	DET
bracis-19081	10	61	latest	late	ADJ
bracis-19081	10	62	articles	article	NOUN
bracis-19081	10	63	,	,	PUNCT
bracis-19081	10	64	books	book	NOUN
bracis-19081	10	65	and	and	CCONJ
bracis-19081	10	66	news	news	NOUN
bracis-19081	10	67	in	in	ADP
bracis-19081	10	68	related	related	ADJ
bracis-19081	10	69	subjects	subject	NOUN
bracis-19081	10	70	,	,	PUNCT
bracis-19081	10	71	suggested	suggest	VERB
bracis-19081	10	72	using	use	VERB
bracis-19081	10	73	machine	machine	NOUN
bracis-19081	10	74	learning	learning	NOUN
bracis-19081	10	75	.	.	PUNCT
bracis-19081	11	1	algorithms	algorithm	NOUN
bracis-19081	11	2	categorization	categorization	NOUN
bracis-19081	11	3	learning	learn	VERB
bracis-19081	11	4	algorithms	algorithm	NOUN
bracis-19081	11	5	machine	machine	NOUN
bracis-19081	11	6	learning	learn	VERB
bracis-19081	11	7	sequence	sequence	NOUN
bracis-19081	11	8	annotation	annotation	NOUN
bracis-19081	11	9	statistical	statistical	ADJ
bracis-19081	11	10	learning	learn	VERB
bracis-19081	11	11	1	1	NUM
bracis-19081	11	12	introduction	introduction	NOUN
bracis-19081	11	13	the	the	DET
bracis-19081	11	14	task	task	NOUN
bracis-19081	11	15	of	of	ADP
bracis-19081	11	16	named	name	VERB
bracis-19081	11	17	entity	entity	NOUN
bracis-19081	11	18	recognition	recognition	NOUN
bracis-19081	11	19	(	(	PUNCT
bracis-19081	11	20	ner	ner	NOUN
bracis-19081	11	21	)	)	PUNCT
bracis-19081	11	22	is	be	AUX
bracis-19081	11	23	widely	widely	ADV
bracis-19081	11	24	used	use	VERB
bracis-19081	11	25	for	for	ADP
bracis-19081	11	26	information	information	NOUN
bracis-19081	11	27	extraction	extraction	NOUN
bracis-19081	11	28	with	with	ADP
bracis-19081	11	29	trained	train	VERB
bracis-19081	11	30	models	model	NOUN
bracis-19081	11	31	being	be	AUX
bracis-19081	11	32	able	able	ADJ
bracis-19081	11	33	to	to	PART
bracis-19081	11	34	directly	directly	ADV
bracis-19081	11	35	extract	extract	VERB
bracis-19081	11	36	named	name	VERB
bracis-19081	11	37	entities	entity	NOUN
bracis-19081	11	38	from	from	ADP
bracis-19081	11	39	unstructured	unstructured	ADJ
bracis-19081	11	40	text	text	NOUN
bracis-19081	11	41	.	.	PUNCT
bracis-19081	12	1	the	the	DET
bracis-19081	12	2	named	name	VERB
bracis-19081	12	3	entities	entity	NOUN
bracis-19081	12	4	can	can	AUX
bracis-19081	12	5	be	be	AUX
bracis-19081	12	6	used	use	VERB
bracis-19081	12	7	to	to	PART
bracis-19081	12	8	create	create	VERB
bracis-19081	12	9	databases	database	NOUN
bracis-19081	12	10	of	of	ADP
bracis-19081	12	11	structured	structured	ADJ
bracis-19081	12	12	information	information	NOUN
bracis-19081	12	13	,	,	PUNCT
bracis-19081	12	14	as	as	ADV
bracis-19081	12	15	well	well	ADV
bracis-19081	12	16	as	as	ADP
bracis-19081	12	17	to	to	PART
bracis-19081	12	18	improve	improve	VERB
bracis-19081	12	19	the	the	DET
bracis-19081	12	20	performance	performance	NOUN
bracis-19081	12	21	of	of	ADP
bracis-19081	12	22	models	model	NOUN
bracis-19081	12	23	in	in	ADP
bracis-19081	12	24	more	more	ADV
bracis-19081	12	25	challenging	challenging	ADJ
bracis-19081	12	26	natural	natural	ADJ
bracis-19081	12	27	language	language	NOUN
bracis-19081	12	28	processing	processing	NOUN
bracis-19081	12	29	tasks	task	NOUN
bracis-19081	12	30	.	.	PUNCT
bracis-19081	13	1	deep	deep	ADJ
bracis-19081	13	2	neural	neural	ADJ
bracis-19081	13	3	models	model	NOUN
bracis-19081	13	4	have	have	AUX
bracis-19081	13	5	been	be	AUX
bracis-19081	13	6	the	the	DET
bracis-19081	13	7	state	state	NOUN
bracis-19081	13	8	of	of	ADP
bracis-19081	13	9	the	the	DET
bracis-19081	13	10	art	art	NOUN
bracis-19081	13	11	for	for	ADP
bracis-19081	13	12	solving	solve	VERB
bracis-19081	13	13	ner	ner	NOUN
bracis-19081	13	14	tasks	task	NOUN
bracis-19081	13	15	,	,	PUNCT
bracis-19081	13	16	but	but	CCONJ
bracis-19081	13	17	to	to	PART
bracis-19081	13	18	be	be	AUX
bracis-19081	13	19	trained	train	VERB
bracis-19081	13	20	to	to	PART
bracis-19081	13	21	achieve	achieve	VERB
bracis-19081	13	22	it	it	PRON
bracis-19081	13	23	they	they	PRON
bracis-19081	13	24	often	often	ADV
bracis-19081	13	25	require	require	VERB
bracis-19081	13	26	big	big	ADJ
bracis-19081	13	27	labeled	label	VERB
bracis-19081	13	28	sets	set	NOUN
bracis-19081	13	29	of	of	ADP
bracis-19081	13	30	data	datum	NOUN
bracis-19081	13	31	.	.	PUNCT
bracis-19081	14	1	in	in	ADP
bracis-19081	14	2	many	many	ADJ
bracis-19081	14	3	practical	practical	ADJ
bracis-19081	14	4	scenarios	scenario	NOUN
bracis-19081	14	5	it	it	PRON
bracis-19081	14	6	’s	’	VERB
bracis-19081	14	7	not	not	PART
bracis-19081	14	8	realistic	realistic	ADJ
bracis-19081	14	9	to	to	PART
bracis-19081	14	10	expect	expect	VERB
bracis-19081	14	11	big	big	ADJ
bracis-19081	14	12	amounts	amount	NOUN
bracis-19081	14	13	of	of	ADP
bracis-19081	14	14	data	datum	NOUN
bracis-19081	14	15	to	to	PART
bracis-19081	14	16	be	be	AUX
bracis-19081	14	17	manually	manually	ADV
bracis-19081	14	18	annotated	annotate	VERB
bracis-19081	14	19	.	.	PUNCT
bracis-19081	15	1	active	active	ADJ
bracis-19081	15	2	learning	learning	NOUN
bracis-19081	15	3	(	(	PUNCT
bracis-19081	15	4	al	al	PROPN
bracis-19081	15	5	)	)	PUNCT
bracis-19081	15	6	algorithms	algorithm	NOUN
bracis-19081	15	7	are	be	AUX
bracis-19081	15	8	often	often	ADV
bracis-19081	15	9	used	use	VERB
bracis-19081	15	10	to	to	PART
bracis-19081	15	11	reduce	reduce	VERB
bracis-19081	15	12	the	the	DET
bracis-19081	15	13	cost	cost	NOUN
bracis-19081	15	14	of	of	ADP
bracis-19081	15	15	annotation	annotation	NOUN
bracis-19081	15	16	by	by	ADP
bracis-19081	15	17	identifying	identify	VERB
bracis-19081	15	18	a	a	DET
bracis-19081	15	19	small	small	ADJ
bracis-19081	15	20	and	and	CCONJ
bracis-19081	15	21	representative	representative	ADJ
bracis-19081	15	22	subset	subset	NOUN
bracis-19081	15	23	of	of	ADP
bracis-19081	15	24	samples	sample	NOUN
bracis-19081	15	25	to	to	PART
bracis-19081	15	26	be	be	AUX
bracis-19081	15	27	labeled	label	VERB
bracis-19081	15	28	.	.	PUNCT
bracis-19081	16	1	it	it	PRON
bracis-19081	16	2	’s	’s	AUX
bracis-19081	16	3	expected	expect	VERB
bracis-19081	16	4	that	that	SCONJ
bracis-19081	16	5	a	a	DET
bracis-19081	16	6	model	model	NOUN
bracis-19081	16	7	trained	train	VERB
bracis-19081	16	8	on	on	ADP
bracis-19081	16	9	this	this	DET
bracis-19081	16	10	representative	representative	NOUN
bracis-19081	16	11	subset	subset	NOUN
bracis-19081	16	12	,	,	PUNCT
bracis-19081	16	13	and	and	CCONJ
bracis-19081	16	14	on	on	ADP
bracis-19081	16	15	the	the	DET
bracis-19081	16	16	whole	whole	ADJ
bracis-19081	16	17	dataset	dataset	NOUN
bracis-19081	16	18	,	,	PUNCT
bracis-19081	16	19	should	should	AUX
bracis-19081	16	20	achieve	achieve	VERB
bracis-19081	16	21	similar	similar	ADJ
bracis-19081	16	22	performances	performance	NOUN
bracis-19081	16	23	.	.	PUNCT
bracis-19081	17	1	thus	thus	ADV
bracis-19081	17	2	,	,	PUNCT
bracis-19081	17	3	by	by	ADP
bracis-19081	17	4	labeling	label	VERB
bracis-19081	17	5	the	the	DET
bracis-19081	17	6	small	small	ADJ
bracis-19081	17	7	representative	representative	NOUN
bracis-19081	17	8	subset	subset	NOUN
bracis-19081	17	9	,	,	PUNCT
bracis-19081	17	10	it	it	PRON
bracis-19081	17	11	is	be	AUX
bracis-19081	17	12	possible	possible	ADJ
bracis-19081	17	13	to	to	PART
bracis-19081	17	14	reduce	reduce	VERB
bracis-19081	17	15	the	the	DET
bracis-19081	17	16	annotation	annotation	NOUN
bracis-19081	17	17	costs	cost	NOUN
bracis-19081	17	18	while	while	SCONJ
bracis-19081	17	19	training	train	VERB
bracis-19081	17	20	a	a	DET
bracis-19081	17	21	good	good	ADJ
bracis-19081	17	22	machine	machine	NOUN
bracis-19081	17	23	learning	learning	NOUN
bracis-19081	17	24	model	model	NOUN
bracis-19081	17	25	.	.	PUNCT
bracis-19081	18	1	deep	deep	ADJ
bracis-19081	18	2	active	active	ADJ
bracis-19081	18	3	learning	learning	NOUN
bracis-19081	18	4	.	.	PUNCT
bracis-19081	19	1	(	(	PUNCT
bracis-19081	19	2	dal	dal	NOUN
bracis-19081	19	3	)	)	PUNCT
bracis-19081	19	4	applied	apply	VERB
bracis-19081	19	5	to	to	ADP
bracis-19081	19	6	sequence	sequence	NOUN
bracis-19081	19	7	tagging	tagging	NOUN
bracis-19081	19	8	tasks	task	NOUN
bracis-19081	19	9	(	(	PUNCT
bracis-19081	19	10	e.g.	e.g.	ADV
bracis-19081	19	11	ner	ner	NOUN
bracis-19081	19	12	,	,	PUNCT
bracis-19081	19	13	pos	pos	NOUN
bracis-19081	19	14	-	-	PUNCT
bracis-19081	19	15	tagging	tagging	NOUN
bracis-19081	19	16	)	)	PUNCT
bracis-19081	19	17	has	have	AUX
bracis-19081	19	18	only	only	ADV
bracis-19081	19	19	recently	recently	ADV
bracis-19081	19	20	appeared	appear	VERB
bracis-19081	19	21	in	in	ADP
bracis-19081	19	22	the	the	DET
bracis-19081	19	23	literature	literature	NOUN
bracis-19081	19	24	[	[	X
bracis-19081	19	25	15	15	NUM
bracis-19081	19	26	]	]	PUNCT
bracis-19081	19	27	,	,	PUNCT
bracis-19081	19	28	even	even	ADV
bracis-19081	19	29	though	though	SCONJ
bracis-19081	19	30	traditional	traditional	ADJ
bracis-19081	19	31	active	active	ADJ
bracis-19081	19	32	learning	learning	NOUN
bracis-19081	19	33	strategies	strategy	NOUN
bracis-19081	19	34	applied	apply	VERB
bracis-19081	19	35	to	to	ADP
bracis-19081	19	36	such	such	ADJ
bracis-19081	19	37	tasks	task	NOUN
bracis-19081	19	38	have	have	AUX
bracis-19081	19	39	appeared	appear	VERB
bracis-19081	19	40	much	much	ADV
bracis-19081	19	41	earlier	early	ADV
bracis-19081	19	42	[	[	X
bracis-19081	19	43	14	14	NUM
bracis-19081	19	44	]	]	PUNCT
bracis-19081	19	45	.	.	PUNCT
bracis-19081	20	1	the	the	DET
bracis-19081	20	2	use	use	NOUN
bracis-19081	20	3	of	of	ADP
bracis-19081	20	4	neural	neural	ADJ
bracis-19081	20	5	-	-	PUNCT
bracis-19081	20	6	based	base	VERB
bracis-19081	20	7	models	model	NOUN
bracis-19081	20	8	in	in	ADP
bracis-19081	20	9	active	active	ADJ
bracis-19081	20	10	learning	learning	NOUN
bracis-19081	20	11	scenarios	scenario	NOUN
bracis-19081	20	12	,	,	PUNCT
bracis-19081	20	13	instead	instead	ADV
bracis-19081	20	14	of	of	ADP
bracis-19081	20	15	classic	classic	ADJ
bracis-19081	20	16	shallow	shallow	ADJ
bracis-19081	20	17	models	model	NOUN
bracis-19081	20	18	,	,	PUNCT
bracis-19081	20	19	brings	bring	VERB
bracis-19081	20	20	with	with	ADP
bracis-19081	20	21	it	it	PRON
bracis-19081	20	22	challenges	challenge	NOUN
bracis-19081	20	23	that	that	PRON
bracis-19081	20	24	need	need	VERB
bracis-19081	20	25	to	to	PART
bracis-19081	20	26	be	be	AUX
bracis-19081	20	27	addressed	address	VERB
bracis-19081	20	28	.	.	PUNCT
bracis-19081	21	1	for	for	ADP
bracis-19081	21	2	once	once	ADV
bracis-19081	21	3	,	,	PUNCT
bracis-19081	21	4	deep	deep	ADJ
bracis-19081	21	5	learning	learning	NOUN
bracis-19081	21	6	models	model	NOUN
bracis-19081	21	7	are	be	AUX
bracis-19081	21	8	slow	slow	ADJ
bracis-19081	21	9	to	to	PART
bracis-19081	21	10	be	be	AUX
bracis-19081	21	11	retrained	retrain	VERB
bracis-19081	21	12	from	from	ADP
bracis-19081	21	13	scratch	scratch	NOUN
bracis-19081	21	14	for	for	ADP
bracis-19081	21	15	each	each	DET
bracis-19081	21	16	active	active	ADJ
bracis-19081	21	17	learning	learn	VERB
bracis-19081	21	18	iteration	iteration	NOUN
bracis-19081	21	19	when	when	SCONJ
bracis-19081	21	20	compared	compare	VERB
bracis-19081	21	21	to	to	ADP
bracis-19081	21	22	shallow	shallow	ADJ
bracis-19081	21	23	models	model	NOUN
bracis-19081	21	24	.	.	PUNCT
bracis-19081	22	1	shen	shen	PROPN
bracis-19081	22	2	et	et	PROPN
bracis-19081	22	3	al	al	PROPN
bracis-19081	22	4	.	.	PUNCT
bracis-19081	23	1	[	[	X
bracis-19081	23	2	15	15	NUM
bracis-19081	23	3	]	]	PUNCT
bracis-19081	23	4	proposes	propose	VERB
bracis-19081	23	5	the	the	DET
bracis-19081	23	6	first	first	ADJ
bracis-19081	23	7	dal	dal	NOUN
bracis-19081	23	8	algorithm	algorithm	NOUN
bracis-19081	23	9	applied	apply	VERB
bracis-19081	23	10	to	to	ADP
bracis-19081	23	11	a	a	DET
bracis-19081	23	12	sequence	sequence	NOUN
bracis-19081	23	13	tagging	tagging	NOUN
bracis-19081	23	14	task	task	NOUN
bracis-19081	23	15	.	.	PUNCT
bracis-19081	24	1	it	it	PRON
bracis-19081	24	2	proposes	propose	VERB
bracis-19081	24	3	to	to	PART
bracis-19081	24	4	use	use	VERB
bracis-19081	24	5	iterative	iterative	NOUN
bracis-19081	24	6	training	training	NOUN
bracis-19081	24	7	where	where	SCONJ
bracis-19081	24	8	the	the	DET
bracis-19081	24	9	neural	neural	ADJ
bracis-19081	24	10	model	model	NOUN
bracis-19081	24	11	’s	’s	PART
bracis-19081	24	12	training	training	NOUN
bracis-19081	24	13	continues	continue	VERB
bracis-19081	24	14	from	from	ADP
bracis-19081	24	15	where	where	SCONJ
bracis-19081	24	16	it	it	PRON
bracis-19081	24	17	stopped	stop	VERB
bracis-19081	24	18	in	in	ADP
bracis-19081	24	19	the	the	DET
bracis-19081	24	20	previous	previous	ADJ
bracis-19081	24	21	iteration	iteration	NOUN
bracis-19081	24	22	of	of	ADP
bracis-19081	24	23	the	the	DET
bracis-19081	24	24	active	active	ADJ
bracis-19081	24	25	learning	learning	NOUN
bracis-19081	24	26	process	process	NOUN
bracis-19081	24	27	.	.	PUNCT
bracis-19081	25	1	this	this	DET
bracis-19081	25	2	iterative	iterative	NOUN
bracis-19081	25	3	training	training	NOUN
bracis-19081	25	4	coupled	couple	VERB
bracis-19081	25	5	with	with	ADP
bracis-19081	25	6	early	early	ADJ
bracis-19081	25	7	stopping	stopping	NOUN
bracis-19081	25	8	based	base	VERB
bracis-19081	25	9	on	on	ADP
bracis-19081	25	10	the	the	DET
bracis-19081	25	11	validation	validation	NOUN
bracis-19081	25	12	set	set	NOUN
bracis-19081	25	13	incurs	incur	VERB
bracis-19081	25	14	in	in	ADP
bracis-19081	25	15	a	a	DET
bracis-19081	25	16	reduction	reduction	NOUN
bracis-19081	25	17	of	of	ADP
bracis-19081	25	18	execution	execution	NOUN
bracis-19081	25	19	time	time	NOUN
bracis-19081	25	20	.	.	PUNCT
bracis-19081	26	1	this	this	PRON
bracis-19081	26	2	may	may	AUX
bracis-19081	26	3	be	be	AUX
bracis-19081	26	4	justified	justify	VERB
bracis-19081	26	5	by	by	ADP
bracis-19081	26	6	the	the	DET
bracis-19081	26	7	fact	fact	NOUN
bracis-19081	26	8	that	that	SCONJ
bracis-19081	26	9	as	as	SCONJ
bracis-19081	26	10	the	the	DET
bracis-19081	26	11	subset	subset	NOUN
bracis-19081	26	12	of	of	ADP
bracis-19081	26	13	labeled	label	VERB
bracis-19081	26	14	samples	sample	NOUN
bracis-19081	26	15	becomes	become	VERB
bracis-19081	26	16	more	more	ADJ
bracis-19081	26	17	representative	representative	NOUN
bracis-19081	26	18	of	of	ADP
bracis-19081	26	19	the	the	DET
bracis-19081	26	20	whole	whole	ADJ
bracis-19081	26	21	dataset	dataset	NOUN
bracis-19081	26	22	,	,	PUNCT
bracis-19081	26	23	new	new	ADJ
bracis-19081	26	24	unlabeled	unlabele	VERB
bracis-19081	26	25	samples	sample	NOUN
bracis-19081	26	26	are	be	AUX
bracis-19081	26	27	less	less	ADV
bracis-19081	26	28	likely	likely	ADJ
bracis-19081	26	29	to	to	PART
bracis-19081	26	30	bring	bring	VERB
bracis-19081	26	31	new	new	ADJ
bracis-19081	26	32	relevant	relevant	ADJ
bracis-19081	26	33	information	information	NOUN
bracis-19081	26	34	to	to	ADP
bracis-19081	26	35	it	it	PRON
bracis-19081	26	36	.	.	PUNCT
bracis-19081	27	1	thus	thus	ADV
bracis-19081	27	2	,	,	PUNCT
bracis-19081	27	3	the	the	DET
bracis-19081	27	4	iteratively	iteratively	ADV
bracis-19081	27	5	trained	train	VERB
bracis-19081	27	6	model	model	NOUN
bracis-19081	27	7	is	be	AUX
bracis-19081	27	8	more	more	ADV
bracis-19081	27	9	likely	likely	ADJ
bracis-19081	27	10	to	to	PART
bracis-19081	27	11	require	require	VERB
bracis-19081	27	12	fewer	few	ADJ
bracis-19081	27	13	training	training	NOUN
bracis-19081	27	14	epochs	epoch	NOUN
bracis-19081	27	15	to	to	PART
bracis-19081	27	16	assimilate	assimilate	VERB
bracis-19081	27	17	the	the	DET
bracis-19081	27	18	newer	new	ADJ
bracis-19081	27	19	samples	sample	NOUN
bracis-19081	27	20	that	that	PRON
bracis-19081	27	21	were	be	AUX
bracis-19081	27	22	recently	recently	ADV
bracis-19081	27	23	labeled	label	VERB
bracis-19081	27	24	.	.	PUNCT
bracis-19081	28	1	they	they	PRON
bracis-19081	28	2	also	also	ADV
bracis-19081	28	3	propose	propose	VERB
bracis-19081	28	4	the	the	DET
bracis-19081	28	5	cnn	cnn	PROPN
bracis-19081	28	6	-	-	PUNCT
bracis-19081	28	7	cnn	cnn	PROPN
bracis-19081	28	8	-	-	PUNCT
bracis-19081	28	9	lstm	lstm	PROPN
bracis-19081	28	10	model	model	NOUN
bracis-19081	28	11	,	,	PUNCT
bracis-19081	28	12	a	a	DET
bracis-19081	28	13	neural	neural	ADJ
bracis-19081	28	14	model	model	NOUN
bracis-19081	28	15	which	which	PRON
bracis-19081	28	16	is	be	AUX
bracis-19081	28	17	lightweight	lightweight	ADJ
bracis-19081	28	18	to	to	PART
bracis-19081	28	19	train	train	VERB
bracis-19081	28	20	and	and	CCONJ
bracis-19081	28	21	the	the	DET
bracis-19081	28	22	maximum	maximum	ADJ
bracis-19081	28	23	normalized	normalize	VERB
bracis-19081	28	24	log	log	NOUN
bracis-19081	28	25	-	-	PUNCT
bracis-19081	28	26	probability	probability	NOUN
bracis-19081	28	27	(	(	PUNCT
bracis-19081	28	28	mnlp	mnlp	ADJ
bracis-19081	28	29	)	)	PUNCT
bracis-19081	28	30	sampling	sample	VERB
bracis-19081	28	31	function	function	NOUN
bracis-19081	28	32	which	which	PRON
bracis-19081	28	33	normalizes	normalize	VERB
bracis-19081	28	34	the	the	DET
bracis-19081	28	35	confidence	confidence	NOUN
bracis-19081	28	36	of	of	ADP
bracis-19081	28	37	the	the	DET
bracis-19081	28	38	model	model	NOUN
bracis-19081	28	39	’s	’s	PART
bracis-19081	28	40	predictions	prediction	NOUN
bracis-19081	28	41	based	base	VERB
bracis-19081	28	42	on	on	ADP
bracis-19081	28	43	the	the	DET
bracis-19081	28	44	sentence	sentence	NOUN
bracis-19081	28	45	’s	’s	PART
bracis-19081	28	46	length	length	NOUN
bracis-19081	28	47	.	.	PUNCT
bracis-19081	29	1	the	the	DET
bracis-19081	29	2	al	al	PROPN
bracis-19081	29	3	algorithm	algorithm	PROPN
bracis-19081	29	4	of	of	ADP
bracis-19081	29	5	shen	shen	PROPN
bracis-19081	29	6	et	et	PROPN
bracis-19081	29	7	al	al	PROPN
bracis-19081	29	8	.	.	PUNCT
bracis-19081	30	1	[	[	X
bracis-19081	30	2	15	15	NUM
bracis-19081	30	3	]	]	X
bracis-19081	30	4	trained	train	VERB
bracis-19081	30	5	a	a	DET
bracis-19081	30	6	neural	neural	ADJ
bracis-19081	30	7	model	model	NOUN
bracis-19081	30	8	to	to	PART
bracis-19081	30	9	peak	peak	VERB
bracis-19081	30	10	performance	performance	NOUN
bracis-19081	30	11	using	use	VERB
bracis-19081	30	12	just	just	ADV
bracis-19081	30	13	over	over	ADP
bracis-19081	30	14	25	25	NUM
bracis-19081	30	15	%	%	NOUN
bracis-19081	30	16	of	of	ADP
bracis-19081	30	17	labeled	label	VERB
bracis-19081	30	18	data	datum	NOUN
bracis-19081	30	19	from	from	ADP
bracis-19081	30	20	the	the	DET
bracis-19081	30	21	training	training	NOUN
bracis-19081	30	22	set	set	NOUN
bracis-19081	30	23	of	of	ADP
bracis-19081	30	24	the	the	DET
bracis-19081	30	25	ontonotes	ontonote	NOUN
bracis-19081	30	26	5.0	5.0	NUM
bracis-19081	30	27	[	[	SYM
bracis-19081	30	28	11	11	NUM
bracis-19081	30	29	]	]	PUNCT
bracis-19081	30	30	dataset	dataset	NOUN
bracis-19081	30	31	.	.	PUNCT
bracis-19081	31	1	siddhant	siddhant	PROPN
bracis-19081	31	2	and	and	CCONJ
bracis-19081	31	3	lipton	lipton	PROPN
bracis-19081	32	1	[	[	X
bracis-19081	32	2	16	16	NUM
bracis-19081	32	3	]	]	PUNCT
bracis-19081	32	4	extend	extend	VERB
bracis-19081	32	5	the	the	DET
bracis-19081	32	6	previous	previous	ADJ
bracis-19081	32	7	work	work	NOUN
bracis-19081	32	8	by	by	ADP
bracis-19081	32	9	shen	shen	PROPN
bracis-19081	32	10	et	et	PROPN
bracis-19081	32	11	al	al	PROPN
bracis-19081	32	12	.	.	PUNCT
bracis-19081	33	1	[	[	X
bracis-19081	33	2	15	15	NUM
bracis-19081	33	3	]	]	PUNCT
bracis-19081	33	4	.	.	PUNCT
bracis-19081	34	1	they	they	PRON
bracis-19081	34	2	rely	rely	VERB
bracis-19081	34	3	on	on	ADP
bracis-19081	34	4	the	the	DET
bracis-19081	34	5	bayesian	bayesian	NOUN
bracis-19081	34	6	active	active	ADJ
bracis-19081	34	7	learning	learn	VERB
bracis-19081	34	8	through	through	ADP
bracis-19081	34	9	disagreement	disagreement	NOUN
bracis-19081	34	10	(	(	PUNCT
bracis-19081	34	11	bald	bald	ADJ
bracis-19081	34	12	)	)	PUNCT
bracis-19081	35	1	[	[	X
bracis-19081	35	2	4	4	X
bracis-19081	35	3	]	]	PUNCT
bracis-19081	35	4	sampling	sample	VERB
bracis-19081	35	5	technique	technique	NOUN
bracis-19081	35	6	,	,	PUNCT
bracis-19081	35	7	which	which	PRON
bracis-19081	35	8	queries	query	VERB
bracis-19081	35	9	unlabeled	unlabele	VERB
bracis-19081	35	10	samples	sample	NOUN
bracis-19081	35	11	that	that	PRON
bracis-19081	35	12	generate	generate	VERB
bracis-19081	35	13	the	the	DET
bracis-19081	35	14	most	most	ADV
bracis-19081	35	15	disagreement	disagreement	NOUN
bracis-19081	35	16	from	from	ADP
bracis-19081	35	17	multiple	multiple	ADJ
bracis-19081	35	18	passes	pass	NOUN
bracis-19081	35	19	on	on	ADP
bracis-19081	35	20	bayesian	bayesian	NOUN
bracis-19081	35	21	neural	neural	ADJ
bracis-19081	35	22	models	model	NOUN
bracis-19081	35	23	and	and	CCONJ
bracis-19081	35	24	apply	apply	VERB
bracis-19081	35	25	it	it	PRON
bracis-19081	35	26	to	to	ADP
bracis-19081	35	27	sequence	sequence	NOUN
bracis-19081	35	28	tagging	tagging	NOUN
bracis-19081	35	29	problems	problem	NOUN
bracis-19081	35	30	.	.	PUNCT
bracis-19081	36	1	they	they	PRON
bracis-19081	36	2	also	also	ADV
bracis-19081	36	3	use	use	VERB
bracis-19081	36	4	early	early	ADJ
bracis-19081	36	5	stopping	stopping	NOUN
bracis-19081	36	6	based	base	VERB
bracis-19081	36	7	on	on	ADP
bracis-19081	36	8	the	the	DET
bracis-19081	36	9	performance	performance	NOUN
bracis-19081	36	10	of	of	ADP
bracis-19081	36	11	the	the	DET
bracis-19081	36	12	model	model	NOUN
bracis-19081	36	13	on	on	ADP
bracis-19081	36	14	the	the	DET
bracis-19081	36	15	validation	validation	NOUN
bracis-19081	36	16	set	set	NOUN
bracis-19081	36	17	,	,	PUNCT
bracis-19081	36	18	but	but	CCONJ
bracis-19081	36	19	limit	limit	VERB
bracis-19081	36	20	the	the	DET
bracis-19081	36	21	size	size	NOUN
bracis-19081	36	22	of	of	ADP
bracis-19081	36	23	the	the	DET
bracis-19081	36	24	validation	validation	NOUN
bracis-19081	36	25	set	set	NOUN
bracis-19081	36	26	for	for	SCONJ
bracis-19081	36	27	it	it	PRON
bracis-19081	36	28	to	to	PART
bracis-19081	36	29	be	be	AUX
bracis-19081	36	30	proportional	proportional	ADJ
bracis-19081	36	31	to	to	ADP
bracis-19081	36	32	the	the	DET
bracis-19081	36	33	size	size	NOUN
bracis-19081	36	34	of	of	ADP
bracis-19081	36	35	the	the	DET
bracis-19081	36	36	labeled	label	VERB
bracis-19081	36	37	set	set	NOUN
bracis-19081	36	38	used	use	VERB
bracis-19081	36	39	to	to	PART
bracis-19081	36	40	train	train	VERB
bracis-19081	36	41	the	the	DET
bracis-19081	36	42	model	model	NOUN
bracis-19081	36	43	.	.	PUNCT
bracis-19081	37	1	the	the	DET
bracis-19081	37	2	experiments	experiment	NOUN
bracis-19081	37	3	performed	perform	VERB
bracis-19081	37	4	investigate	investigate	VERB
bracis-19081	37	5	the	the	DET
bracis-19081	37	6	performance	performance	NOUN
bracis-19081	37	7	of	of	ADP
bracis-19081	37	8	the	the	DET
bracis-19081	37	9	bayesian	bayesian	NOUN
bracis-19081	37	10	dal	dal	NOUN
bracis-19081	37	11	algorithm	algorithm	NOUN
bracis-19081	37	12	proposed	propose	VERB
bracis-19081	37	13	using	use	VERB
bracis-19081	37	14	the	the	DET
bracis-19081	37	15	cnn	cnn	PROPN
bracis-19081	37	16	-	-	PUNCT
bracis-19081	37	17	cnn	cnn	PROPN
bracis-19081	37	18	-	-	PUNCT
bracis-19081	37	19	lstm	lstm	NOUN
bracis-19081	37	20	[	[	X
bracis-19081	37	21	15	15	NUM
bracis-19081	37	22	]	]	PUNCT
bracis-19081	37	23	and	and	CCONJ
bracis-19081	37	24	the	the	DET
bracis-19081	37	25	cnn	cnn	PROPN
bracis-19081	37	26	-	-	PUNCT
bracis-19081	37	27	bilstm	bilstm	NOUN
bracis-19081	37	28	-	-	PUNCT
bracis-19081	37	29	crf	crf	NOUN
bracis-19081	38	1	[	[	X
bracis-19081	38	2	7	7	NUM
bracis-19081	38	3	]	]	ADJ
bracis-19081	38	4	models	model	NOUN
bracis-19081	38	5	on	on	ADP
bracis-19081	38	6	the	the	DET
bracis-19081	38	7	ontonotes	ontonote	NOUN
bracis-19081	38	8	5.0	5.0	NUM
bracis-19081	38	9	and	and	CCONJ
bracis-19081	38	10	conll	conll	NOUN
bracis-19081	38	11	2003	2003	NUM
bracis-19081	38	12	[	[	X
bracis-19081	38	13	13	13	NUM
bracis-19081	38	14	]	]	PUNCT
bracis-19081	38	15	datasets	dataset	NOUN
bracis-19081	38	16	.	.	PUNCT
bracis-19081	39	1	the	the	DET
bracis-19081	39	2	results	result	NOUN
bracis-19081	39	3	indicate	indicate	VERB
bracis-19081	39	4	that	that	SCONJ
bracis-19081	39	5	the	the	DET
bracis-19081	39	6	proposed	propose	VERB
bracis-19081	39	7	bayesian	bayesian	NOUN
bracis-19081	39	8	sampling	sampling	NOUN
bracis-19081	39	9	functions	function	NOUN
bracis-19081	39	10	consistently	consistently	ADV
bracis-19081	39	11	outperform	outperform	VERB
bracis-19081	39	12	the	the	DET
bracis-19081	39	13	mnlp	mnlp	ADJ
bracis-19081	39	14	function	function	NOUN
bracis-19081	39	15	,	,	PUNCT
bracis-19081	39	16	but	but	CCONJ
bracis-19081	39	17	with	with	ADP
bracis-19081	39	18	marginal	marginal	ADJ
bracis-19081	39	19	improvement	improvement	NOUN
bracis-19081	39	20	.	.	PUNCT
bracis-19081	40	1	current	current	ADJ
bracis-19081	40	2	works	work	NOUN
bracis-19081	40	3	on	on	ADP
bracis-19081	40	4	deep	deep	ADJ
bracis-19081	40	5	active	active	ADJ
bracis-19081	40	6	learning	learning	NOUN
bracis-19081	40	7	applied	apply	VERB
bracis-19081	40	8	to	to	ADP
bracis-19081	40	9	ner	ner	NOUN
bracis-19081	40	10	rely	rely	VERB
bracis-19081	40	11	on	on	ADP
bracis-19081	40	12	validation	validation	NOUN
bracis-19081	40	13	sets	set	NOUN
bracis-19081	40	14	for	for	ADP
bracis-19081	40	15	early	early	ADJ
bracis-19081	40	16	stopping	stopping	NOUN
bracis-19081	40	17	of	of	ADP
bracis-19081	40	18	the	the	DET
bracis-19081	40	19	model	model	NOUN
bracis-19081	40	20	training	training	NOUN
bracis-19081	40	21	.	.	PUNCT
bracis-19081	41	1	in	in	ADP
bracis-19081	41	2	real	real	ADJ
bracis-19081	41	3	world	world	NOUN
bracis-19081	41	4	scenarios	scenario	NOUN
bracis-19081	41	5	,	,	PUNCT
bracis-19081	41	6	active	active	ADJ
bracis-19081	41	7	learning	learning	NOUN
bracis-19081	41	8	algorithms	algorithm	NOUN
bracis-19081	41	9	are	be	AUX
bracis-19081	41	10	used	use	VERB
bracis-19081	41	11	to	to	PART
bracis-19081	41	12	reduce	reduce	VERB
bracis-19081	41	13	annotation	annotation	NOUN
bracis-19081	41	14	costs	cost	NOUN
bracis-19081	41	15	,	,	PUNCT
bracis-19081	41	16	and	and	CCONJ
bracis-19081	41	17	separating	separate	VERB
bracis-19081	41	18	a	a	DET
bracis-19081	41	19	part	part	NOUN
bracis-19081	41	20	of	of	ADP
bracis-19081	41	21	the	the	DET
bracis-19081	41	22	labeled	label	VERB
bracis-19081	41	23	dataset	dataset	NOUN
bracis-19081	41	24	to	to	PART
bracis-19081	41	25	be	be	AUX
bracis-19081	41	26	used	use	VERB
bracis-19081	41	27	as	as	ADP
bracis-19081	41	28	a	a	DET
bracis-19081	41	29	validation	validation	NOUN
bracis-19081	41	30	set	set	NOUN
bracis-19081	41	31	seems	seem	VERB
bracis-19081	41	32	to	to	PART
bracis-19081	41	33	go	go	VERB
bracis-19081	41	34	against	against	ADP
bracis-19081	41	35	the	the	DET
bracis-19081	41	36	core	core	ADJ
bracis-19081	41	37	idea	idea	NOUN
bracis-19081	41	38	of	of	ADP
bracis-19081	41	39	al	al	PROPN
bracis-19081	41	40	in	in	ADP
bracis-19081	41	41	general	general	ADJ
bracis-19081	41	42	.	.	PUNCT
bracis-19081	42	1	active	active	ADJ
bracis-19081	42	2	-	-	PUNCT
bracis-19081	42	3	self	self	NOUN
bracis-19081	42	4	learning	learning	NOUN
bracis-19081	42	5	.	.	PUNCT
bracis-19081	43	1	(	(	PUNCT
bracis-19081	43	2	asl	asl	NOUN
bracis-19081	43	3	)	)	PUNCT
bracis-19081	43	4	combines	combine	VERB
bracis-19081	43	5	traditional	traditional	ADJ
bracis-19081	43	6	active	active	ADJ
bracis-19081	43	7	learning	learning	NOUN
bracis-19081	43	8	with	with	ADP
bracis-19081	43	9	self	self	NOUN
bracis-19081	43	10	-	-	PUNCT
bracis-19081	43	11	training	training	NOUN
bracis-19081	43	12	techniques	technique	NOUN
bracis-19081	43	13	,	,	PUNCT
bracis-19081	43	14	where	where	SCONJ
bracis-19081	43	15	an	an	DET
bracis-19081	43	16	oracle	oracle	NOUN
bracis-19081	43	17	(	(	PUNCT
bracis-19081	43	18	i.e.	i.e.	X
bracis-19081	43	19	human	human	ADJ
bracis-19081	43	20	annotator	annotator	NOUN
bracis-19081	43	21	)	)	PUNCT
bracis-19081	43	22	annotates	annotate	VERB
bracis-19081	43	23	the	the	DET
bracis-19081	43	24	most	most	ADV
bracis-19081	43	25	informative	informative	ADJ
bracis-19081	43	26	samples	sample	NOUN
bracis-19081	43	27	queried	query	VERB
bracis-19081	43	28	by	by	ADP
bracis-19081	43	29	a	a	DET
bracis-19081	43	30	sampling	sample	VERB
bracis-19081	43	31	function	function	NOUN
bracis-19081	43	32	(	(	PUNCT
bracis-19081	43	33	e.g.	e.g.	ADV
bracis-19081	43	34	least	least	ADJ
bracis-19081	43	35	confidence	confidence	NOUN
bracis-19081	43	36	,	,	PUNCT
bracis-19081	43	37	mnlp	mnlp	ADJ
bracis-19081	43	38	)	)	PUNCT
bracis-19081	43	39	while	while	SCONJ
bracis-19081	43	40	the	the	DET
bracis-19081	43	41	trained	train	VERB
bracis-19081	43	42	model	model	NOUN
bracis-19081	43	43	labels	label	VERB
bracis-19081	43	44	samples	sample	NOUN
bracis-19081	43	45	for	for	ADP
bracis-19081	43	46	which	which	PRON
bracis-19081	43	47	it	it	PRON
bracis-19081	43	48	has	have	VERB
bracis-19081	43	49	the	the	DET
bracis-19081	43	50	highest	high	ADJ
bracis-19081	43	51	confidence	confidence	NOUN
bracis-19081	43	52	in	in	ADP
bracis-19081	43	53	its	its	PRON
bracis-19081	43	54	predictions	prediction	NOUN
bracis-19081	43	55	.	.	PUNCT
bracis-19081	44	1	the	the	DET
bracis-19081	44	2	asl	asl	PROPN
bracis-19081	44	3	algorithm	algorithm	NOUN
bracis-19081	44	4	comes	come	VERB
bracis-19081	44	5	to	to	PART
bracis-19081	44	6	further	far	ADV
bracis-19081	44	7	reduce	reduce	VERB
bracis-19081	44	8	the	the	DET
bracis-19081	44	9	costs	cost	NOUN
bracis-19081	44	10	of	of	ADP
bracis-19081	44	11	labeling	label	VERB
bracis-19081	44	12	a	a	DET
bracis-19081	44	13	dataset	dataset	NOUN
bracis-19081	44	14	,	,	PUNCT
bracis-19081	44	15	when	when	SCONJ
bracis-19081	44	16	compared	compare	VERB
bracis-19081	44	17	to	to	ADP
bracis-19081	44	18	the	the	DET
bracis-19081	44	19	pure	pure	ADJ
bracis-19081	44	20	active	active	ADJ
bracis-19081	44	21	learning	learning	NOUN
bracis-19081	44	22	process	process	NOUN
bracis-19081	44	23	.	.	PUNCT
bracis-19081	45	1	tran	tran	PROPN
bracis-19081	45	2	et	et	PROPN
bracis-19081	45	3	al	al	PROPN
bracis-19081	45	4	.	.	PUNCT
bracis-19081	46	1	[	[	X
bracis-19081	46	2	17	17	NUM
bracis-19081	46	3	]	]	PUNCT
bracis-19081	46	4	shows	show	VERB
bracis-19081	46	5	that	that	SCONJ
bracis-19081	46	6	the	the	DET
bracis-19081	46	7	symbiotic	symbiotic	ADJ
bracis-19081	46	8	relationship	relationship	NOUN
bracis-19081	46	9	created	create	VERB
bracis-19081	46	10	by	by	ADP
bracis-19081	46	11	both	both	CCONJ
bracis-19081	46	12	the	the	DET
bracis-19081	46	13	human	human	NOUN
bracis-19081	46	14	and	and	CCONJ
bracis-19081	46	15	a	a	DET
bracis-19081	46	16	trained	train	VERB
bracis-19081	46	17	conditional	conditional	ADJ
bracis-19081	46	18	random	random	ADJ
bracis-19081	46	19	field	field	NOUN
bracis-19081	46	20	model	model	NOUN
bracis-19081	46	21	,	,	PUNCT
bracis-19081	46	22	labeling	label	VERB
bracis-19081	46	23	samples	sample	NOUN
bracis-19081	46	24	from	from	ADP
bracis-19081	46	25	the	the	DET
bracis-19081	46	26	unlabeled	unlabele	VERB
bracis-19081	46	27	set	set	NOUN
bracis-19081	46	28	,	,	PUNCT
bracis-19081	46	29	increases	increase	VERB
bracis-19081	46	30	the	the	DET
bracis-19081	46	31	performance	performance	NOUN
bracis-19081	46	32	of	of	ADP
bracis-19081	46	33	the	the	DET
bracis-19081	46	34	model	model	NOUN
bracis-19081	46	35	while	while	SCONJ
bracis-19081	46	36	significantly	significantly	ADV
bracis-19081	46	37	reduce	reduce	VERB
bracis-19081	46	38	labeling	labeling	NOUN
bracis-19081	46	39	costs	cost	NOUN
bracis-19081	46	40	.	.	PUNCT
bracis-19081	47	1	one	one	NUM
bracis-19081	47	2	major	major	ADJ
bracis-19081	47	3	drawback	drawback	NOUN
bracis-19081	47	4	of	of	ADP
bracis-19081	47	5	the	the	DET
bracis-19081	47	6	asl	asl	PROPN
bracis-19081	47	7	algorithm	algorithm	NOUN
bracis-19081	47	8	appears	appear	VERB
bracis-19081	47	9	in	in	ADP
bracis-19081	47	10	its	its	PRON
bracis-19081	47	11	sensitivity	sensitivity	NOUN
bracis-19081	47	12	to	to	ADP
bracis-19081	47	13	the	the	DET
bracis-19081	47	14	quality	quality	NOUN
bracis-19081	47	15	of	of	ADP
bracis-19081	47	16	the	the	DET
bracis-19081	47	17	initial	initial	ADJ
bracis-19081	47	18	labeled	label	VERB
bracis-19081	47	19	set	set	NOUN
bracis-19081	47	20	,	,	PUNCT
bracis-19081	47	21	where	where	SCONJ
bracis-19081	47	22	a	a	DET
bracis-19081	47	23	model	model	NOUN
bracis-19081	47	24	trained	train	VERB
bracis-19081	47	25	on	on	ADP
bracis-19081	47	26	an	an	DET
bracis-19081	47	27	ill	ill	ADV
bracis-19081	47	28	-	-	PUNCT
bracis-19081	47	29	sampled	sample	VERB
bracis-19081	47	30	initial	initial	ADJ
bracis-19081	47	31	labeled	label	VERB
bracis-19081	47	32	set	set	NOUN
bracis-19081	47	33	can	can	AUX
bracis-19081	47	34	have	have	VERB
bracis-19081	47	35	its	its	PRON
bracis-19081	47	36	performance	performance	NOUN
bracis-19081	47	37	significantly	significantly	ADV
bracis-19081	47	38	reduced	reduce	VERB
bracis-19081	47	39	throughout	throughout	ADP
bracis-19081	47	40	the	the	DET
bracis-19081	47	41	asl	asl	NOUN
bracis-19081	47	42	process	process	NOUN
bracis-19081	47	43	.	.	PUNCT
bracis-19081	48	1	in	in	ADP
bracis-19081	48	2	this	this	DET
bracis-19081	48	3	work	work	NOUN
bracis-19081	48	4	,	,	PUNCT
bracis-19081	48	5	we	we	PRON
bracis-19081	48	6	propose	propose	VERB
bracis-19081	48	7	a	a	DET
bracis-19081	48	8	deep	deep	ADJ
bracis-19081	48	9	active	active	ADJ
bracis-19081	48	10	-	-	PUNCT
bracis-19081	48	11	self	self	NOUN
bracis-19081	48	12	learning	learn	VERB
bracis-19081	48	13	algorithm	algorithm	NOUN
bracis-19081	48	14	,	,	PUNCT
bracis-19081	48	15	that	that	PRON
bracis-19081	48	16	builds	build	VERB
bracis-19081	48	17	upon	upon	SCONJ
bracis-19081	48	18	previous	previous	ADJ
bracis-19081	48	19	works	work	NOUN
bracis-19081	48	20	from	from	ADP
bracis-19081	48	21	the	the	DET
bracis-19081	48	22	literature	literature	NOUN
bracis-19081	48	23	[	[	X
bracis-19081	48	24	6	6	NUM
bracis-19081	48	25	,	,	PUNCT
bracis-19081	48	26	17	17	NUM
bracis-19081	48	27	]	]	PUNCT
bracis-19081	48	28	.	.	PUNCT
bracis-19081	49	1	we	we	PRON
bracis-19081	49	2	propose	propose	VERB
bracis-19081	49	3	some	some	DET
bracis-19081	49	4	key	key	ADJ
bracis-19081	49	5	changes	change	NOUN
bracis-19081	49	6	to	to	ADP
bracis-19081	49	7	the	the	DET
bracis-19081	49	8	algorithm	algorithm	NOUN
bracis-19081	49	9	from	from	ADP
bracis-19081	49	10	the	the	DET
bracis-19081	49	11	literature	literature	NOUN
bracis-19081	49	12	in	in	ADP
bracis-19081	49	13	order	order	NOUN
bracis-19081	49	14	to	to	PART
bracis-19081	49	15	try	try	VERB
bracis-19081	49	16	and	and	CCONJ
bracis-19081	49	17	minimize	minimize	VERB
bracis-19081	49	18	its	its	PRON
bracis-19081	49	19	sensitivity	sensitivity	NOUN
bracis-19081	49	20	to	to	ADP
bracis-19081	49	21	the	the	DET
bracis-19081	49	22	initial	initial	ADJ
bracis-19081	49	23	set	set	NOUN
bracis-19081	49	24	of	of	ADP
bracis-19081	49	25	labeled	label	VERB
bracis-19081	49	26	samples	sample	NOUN
bracis-19081	49	27	.	.	PUNCT
bracis-19081	50	1	we	we	PRON
bracis-19081	50	2	also	also	ADV
bracis-19081	50	3	propose	propose	VERB
bracis-19081	50	4	an	an	DET
bracis-19081	50	5	early	early	ADJ
bracis-19081	50	6	stopping	stopping	NOUN
bracis-19081	50	7	strategy	strategy	NOUN
bracis-19081	50	8	based	base	VERB
bracis-19081	50	9	on	on	ADP
bracis-19081	50	10	the	the	DET
bracis-19081	50	11	model	model	NOUN
bracis-19081	50	12	’s	’s	PART
bracis-19081	50	13	confidence	confidence	NOUN
bracis-19081	50	14	on	on	ADP
bracis-19081	50	15	an	an	DET
bracis-19081	50	16	unlabeled	unlabele	VERB
bracis-19081	50	17	set	set	NOUN
bracis-19081	50	18	,	,	PUNCT
bracis-19081	50	19	which	which	PRON
bracis-19081	50	20	renders	render	VERB
bracis-19081	50	21	the	the	DET
bracis-19081	50	22	use	use	NOUN
bracis-19081	50	23	of	of	ADP
bracis-19081	50	24	a	a	DET
bracis-19081	50	25	validation	validation	NOUN
bracis-19081	50	26	set	set	NOUN
bracis-19081	50	27	unnecessary	unnecessary	ADJ
bracis-19081	50	28	.	.	PUNCT
bracis-19081	51	1	2	2	NUM
bracis-19081	51	2	methodology	methodology	NOUN
bracis-19081	51	3	this	this	DET
bracis-19081	51	4	section	section	NOUN
bracis-19081	51	5	presents	present	VERB
bracis-19081	51	6	the	the	DET
bracis-19081	51	7	proposed	propose	VERB
bracis-19081	51	8	deep	deep	ADJ
bracis-19081	51	9	active	active	ADJ
bracis-19081	51	10	-	-	PUNCT
bracis-19081	51	11	self	self	NOUN
bracis-19081	51	12	learning	learn	VERB
bracis-19081	51	13	algorithm	algorithm	NOUN
bracis-19081	51	14	,	,	PUNCT
bracis-19081	51	15	which	which	PRON
bracis-19081	51	16	extends	extend	VERB
bracis-19081	51	17	previous	previous	ADJ
bracis-19081	51	18	works	work	NOUN
bracis-19081	51	19	from	from	ADP
bracis-19081	51	20	the	the	DET
bracis-19081	51	21	literature	literature	NOUN
bracis-19081	51	22	[	[	X
bracis-19081	51	23	6	6	NUM
bracis-19081	51	24	,	,	PUNCT
bracis-19081	51	25	17	17	NUM
bracis-19081	51	26	]	]	PUNCT
bracis-19081	51	27	with	with	ADP
bracis-19081	51	28	the	the	DET
bracis-19081	51	29	use	use	NOUN
bracis-19081	51	30	of	of	ADP
bracis-19081	51	31	deep	deep	ADJ
bracis-19081	51	32	learning	learning	NOUN
bracis-19081	51	33	models	model	NOUN
bracis-19081	51	34	and	and	CCONJ
bracis-19081	51	35	key	key	ADJ
bracis-19081	51	36	changes	change	NOUN
bracis-19081	51	37	to	to	PART
bracis-19081	51	38	alleviate	alleviate	VERB
bracis-19081	51	39	the	the	DET
bracis-19081	51	40	sensitivity	sensitivity	NOUN
bracis-19081	51	41	of	of	ADP
bracis-19081	51	42	the	the	DET
bracis-19081	51	43	self	self	NOUN
bracis-19081	51	44	learning	learn	VERB
bracis-19081	51	45	process	process	NOUN
bracis-19081	51	46	to	to	ADP
bracis-19081	51	47	the	the	DET
bracis-19081	51	48	initial	initial	ADJ
bracis-19081	51	49	labeled	label	VERB
bracis-19081	51	50	set	set	NOUN
bracis-19081	51	51	.	.	PUNCT
bracis-19081	52	1	along	along	ADP
bracis-19081	52	2	with	with	ADP
bracis-19081	52	3	the	the	DET
bracis-19081	52	4	asl	asl	NOUN
bracis-19081	52	5	algorithm	algorithm	NOUN
bracis-19081	52	6	,	,	PUNCT
bracis-19081	52	7	we	we	PRON
bracis-19081	52	8	also	also	ADV
bracis-19081	52	9	propose	propose	VERB
bracis-19081	52	10	an	an	DET
bracis-19081	52	11	early	early	ADJ
bracis-19081	52	12	stopping	stopping	NOUN
bracis-19081	52	13	criterion	criterion	NOUN
bracis-19081	52	14	based	base	VERB
bracis-19081	52	15	on	on	ADP
bracis-19081	52	16	the	the	DET
bracis-19081	52	17	model	model	NOUN
bracis-19081	52	18	’s	’s	PART
bracis-19081	52	19	confidence	confidence	NOUN
bracis-19081	52	20	on	on	ADP
bracis-19081	52	21	its	its	PRON
bracis-19081	52	22	predictions	prediction	NOUN
bracis-19081	52	23	for	for	ADP
bracis-19081	52	24	the	the	DET
bracis-19081	52	25	unlabeled	unlabeled	ADJ
bracis-19081	52	26	samples	sample	NOUN
bracis-19081	52	27	,	,	PUNCT
bracis-19081	52	28	effectively	effectively	ADV
bracis-19081	52	29	dismissing	dismiss	VERB
bracis-19081	52	30	the	the	DET
bracis-19081	52	31	use	use	NOUN
bracis-19081	52	32	of	of	ADP
bracis-19081	52	33	a	a	DET
bracis-19081	52	34	validation	validation	NOUN
bracis-19081	52	35	set	set	VERB
bracis-19081	52	36	throughout	throughout	ADP
bracis-19081	52	37	the	the	DET
bracis-19081	52	38	asl	asl	NOUN
bracis-19081	52	39	procedure	procedure	NOUN
bracis-19081	52	40	.	.	PUNCT
bracis-19081	53	1	sections	section	NOUN
bracis-19081	53	2	 	 	SPACE
bracis-19081	53	3	2.1	2.1	NUM
bracis-19081	53	4	and	and	CCONJ
bracis-19081	53	5	2.2	2.2	NUM
bracis-19081	53	6	present	present	NOUN
bracis-19081	53	7	the	the	DET
bracis-19081	53	8	proposed	propose	VERB
bracis-19081	53	9	asl	asl	NOUN
bracis-19081	53	10	algorithm	algorithm	NOUN
bracis-19081	53	11	and	and	CCONJ
bracis-19081	53	12	the	the	DET
bracis-19081	53	13	early	early	ADJ
bracis-19081	53	14	stopping	stopping	NOUN
bracis-19081	53	15	criterion	criterion	NOUN
bracis-19081	53	16	,	,	PUNCT
bracis-19081	53	17	respectively	respectively	ADV
bracis-19081	53	18	.	.	PUNCT
bracis-19081	54	1	section	section	NOUN
bracis-19081	54	2	 	 	SPACE
bracis-19081	54	3	2.3	2.3	NUM
bracis-19081	54	4	presents	present	VERB
bracis-19081	54	5	the	the	DET
bracis-19081	54	6	experiments	experiment	NOUN
bracis-19081	54	7	to	to	PART
bracis-19081	54	8	be	be	AUX
bracis-19081	54	9	performed	perform	VERB
bracis-19081	54	10	to	to	PART
bracis-19081	54	11	evaluate	evaluate	VERB
bracis-19081	54	12	the	the	DET
bracis-19081	54	13	proposed	propose	VERB
bracis-19081	54	14	strategies	strategy	NOUN
bracis-19081	54	15	,	,	PUNCT
bracis-19081	54	16	as	as	ADV
bracis-19081	54	17	well	well	ADV
bracis-19081	54	18	as	as	ADP
bracis-19081	54	19	the	the	DET
bracis-19081	54	20	baselines	baseline	NOUN
bracis-19081	54	21	for	for	ADP
bracis-19081	54	22	comparison	comparison	NOUN
bracis-19081	54	23	and	and	CCONJ
bracis-19081	54	24	hardware	hardware	NOUN
bracis-19081	54	25	setup	setup	NOUN
bracis-19081	54	26	used	use	VERB
bracis-19081	54	27	for	for	ADP
bracis-19081	54	28	simulations	simulation	NOUN
bracis-19081	54	29	.	.	PUNCT
bracis-19081	55	1	2.1	2.1	NUM
bracis-19081	55	2	deep	deep	ADJ
bracis-19081	55	3	active	active	ADJ
bracis-19081	55	4	-	-	PUNCT
bracis-19081	55	5	self	self	NOUN
bracis-19081	55	6	learning	learn	VERB
bracis-19081	55	7	algorithm	algorithm	NOUN
bracis-19081	55	8	the	the	DET
bracis-19081	55	9	active	active	ADJ
bracis-19081	55	10	-	-	PUNCT
bracis-19081	55	11	self	self	NOUN
bracis-19081	55	12	learning	learn	VERB
bracis-19081	55	13	algorithms	algorithm	NOUN
bracis-19081	55	14	from	from	ADP
bracis-19081	55	15	the	the	DET
bracis-19081	55	16	literature	literature	NOUN
bracis-19081	55	17	require	require	VERB
bracis-19081	55	18	the	the	DET
bracis-19081	55	19	human	human	NOUN
bracis-19081	55	20	and	and	CCONJ
bracis-19081	55	21	the	the	DET
bracis-19081	55	22	trained	train	VERB
bracis-19081	55	23	model	model	NOUN
bracis-19081	55	24	to	to	PART
bracis-19081	55	25	cooperatively	cooperatively	ADV
bracis-19081	55	26	annotate	annotate	VERB
bracis-19081	55	27	samples	sample	NOUN
bracis-19081	55	28	from	from	ADP
bracis-19081	55	29	the	the	DET
bracis-19081	55	30	unlabeled	unlabele	VERB
bracis-19081	55	31	set	set	NOUN
bracis-19081	55	32	.	.	PUNCT
bracis-19081	56	1	this	this	DET
bracis-19081	56	2	process	process	NOUN
bracis-19081	56	3	is	be	AUX
bracis-19081	56	4	very	very	ADV
bracis-19081	56	5	sensitive	sensitive	ADJ
bracis-19081	56	6	to	to	ADP
bracis-19081	56	7	the	the	DET
bracis-19081	56	8	initial	initial	ADJ
bracis-19081	56	9	labeled	label	VERB
bracis-19081	56	10	set	set	NOUN
bracis-19081	56	11	,	,	PUNCT
bracis-19081	56	12	which	which	PRON
bracis-19081	56	13	is	be	AUX
bracis-19081	56	14	used	use	VERB
bracis-19081	56	15	to	to	PART
bracis-19081	56	16	train	train	VERB
bracis-19081	56	17	the	the	DET
bracis-19081	56	18	initial	initial	ADJ
bracis-19081	56	19	machine	machine	NOUN
bracis-19081	56	20	learning	learning	NOUN
bracis-19081	56	21	model	model	NOUN
bracis-19081	56	22	[	[	X
bracis-19081	56	23	17	17	NUM
bracis-19081	56	24	]	]	PUNCT
bracis-19081	56	25	.	.	PUNCT
bracis-19081	57	1	we	we	PRON
bracis-19081	57	2	argue	argue	VERB
bracis-19081	57	3	that	that	SCONJ
bracis-19081	57	4	this	this	DET
bracis-19081	57	5	sensitivity	sensitivity	NOUN
bracis-19081	57	6	comes	come	VERB
bracis-19081	57	7	from	from	ADP
bracis-19081	57	8	the	the	DET
bracis-19081	57	9	fact	fact	NOUN
bracis-19081	57	10	that	that	SCONJ
bracis-19081	57	11	samples	sample	NOUN
bracis-19081	57	12	annotated	annotate	VERB
bracis-19081	57	13	by	by	ADP
bracis-19081	57	14	the	the	DET
bracis-19081	57	15	model	model	NOUN
bracis-19081	57	16	in	in	ADP
bracis-19081	57	17	early	early	ADJ
bracis-19081	57	18	rounds	round	NOUN
bracis-19081	57	19	of	of	ADP
bracis-19081	57	20	the	the	DET
bracis-19081	57	21	asl	asl	PROPN
bracis-19081	57	22	algorithm	algorithm	NOUN
bracis-19081	57	23	may	may	AUX
bracis-19081	57	24	add	add	VERB
bracis-19081	57	25	a	a	DET
bracis-19081	57	26	permanent	permanent	ADJ
bracis-19081	57	27	bias	bias	NOUN
bracis-19081	57	28	to	to	ADP
bracis-19081	57	29	the	the	DET
bracis-19081	57	30	labeled	label	VERB
bracis-19081	57	31	set	set	NOUN
bracis-19081	57	32	,	,	PUNCT
bracis-19081	57	33	if	if	SCONJ
bracis-19081	57	34	poorly	poorly	ADV
bracis-19081	57	35	annotated	annotate	VERB
bracis-19081	57	36	.	.	PUNCT
bracis-19081	58	1	this	this	PRON
bracis-19081	58	2	stems	stem	VERB
bracis-19081	58	3	from	from	ADP
bracis-19081	58	4	the	the	DET
bracis-19081	58	5	fact	fact	NOUN
bracis-19081	58	6	that	that	SCONJ
bracis-19081	58	7	the	the	DET
bracis-19081	58	8	samples	sample	NOUN
bracis-19081	58	9	annotated	annotate	VERB
bracis-19081	58	10	by	by	ADP
bracis-19081	58	11	the	the	DET
bracis-19081	58	12	model	model	NOUN
bracis-19081	58	13	are	be	AUX
bracis-19081	58	14	considered	consider	VERB
bracis-19081	58	15	as	as	ADV
bracis-19081	58	16	reliable	reliable	ADJ
bracis-19081	58	17	as	as	ADP
bracis-19081	58	18	those	those	PRON
bracis-19081	58	19	annotated	annotate	VERB
bracis-19081	58	20	by	by	ADP
bracis-19081	58	21	the	the	DET
bracis-19081	58	22	oracle	oracle	NOUN
bracis-19081	58	23	.	.	PUNCT
bracis-19081	59	1	based	base	VERB
bracis-19081	59	2	on	on	ADP
bracis-19081	59	3	that	that	PRON
bracis-19081	59	4	,	,	PUNCT
bracis-19081	59	5	we	we	PRON
bracis-19081	59	6	propose	propose	VERB
bracis-19081	59	7	an	an	DET
bracis-19081	59	8	active	active	ADJ
bracis-19081	59	9	-	-	PUNCT
bracis-19081	59	10	self	self	NOUN
bracis-19081	59	11	learning	learn	VERB
bracis-19081	59	12	algorithm	algorithm	NOUN
bracis-19081	59	13	that	that	PRON
bracis-19081	59	14	separates	separate	VERB
bracis-19081	59	15	samples	sample	NOUN
bracis-19081	59	16	labeled	label	VERB
bracis-19081	59	17	by	by	ADP
bracis-19081	59	18	the	the	DET
bracis-19081	59	19	model	model	NOUN
bracis-19081	59	20	from	from	ADP
bracis-19081	59	21	those	those	PRON
bracis-19081	59	22	labeled	label	VERB
bracis-19081	59	23	by	by	ADP
bracis-19081	59	24	the	the	DET
bracis-19081	59	25	human	human	ADJ
bracis-19081	59	26	annotator	annotator	NOUN
bracis-19081	59	27	,	,	PUNCT
bracis-19081	59	28	with	with	ADP
bracis-19081	59	29	the	the	DET
bracis-19081	59	30	former	former	ADJ
bracis-19081	59	31	having	have	VERB
bracis-19081	59	32	less	less	ADJ
bracis-19081	59	33	impact	impact	NOUN
bracis-19081	59	34	on	on	ADP
bracis-19081	59	35	the	the	DET
bracis-19081	59	36	model	model	NOUN
bracis-19081	59	37	’s	’s	PART
bracis-19081	59	38	parameters	parameter	NOUN
bracis-19081	59	39	during	during	ADP
bracis-19081	59	40	training	training	NOUN
bracis-19081	59	41	.	.	PUNCT
bracis-19081	60	1	we	we	PRON
bracis-19081	60	2	also	also	ADV
bracis-19081	60	3	propose	propose	VERB
bracis-19081	60	4	to	to	PART
bracis-19081	60	5	return	return	VERB
bracis-19081	60	6	the	the	DET
bracis-19081	60	7	samples	sample	NOUN
bracis-19081	60	8	labeled	label	VERB
bracis-19081	60	9	by	by	ADP
bracis-19081	60	10	the	the	DET
bracis-19081	60	11	model	model	NOUN
bracis-19081	60	12	to	to	ADP
bracis-19081	60	13	the	the	DET
bracis-19081	60	14	unlabeled	unlabele	VERB
bracis-19081	60	15	set	set	VERB
bracis-19081	60	16	at	at	ADP
bracis-19081	60	17	the	the	DET
bracis-19081	60	18	end	end	NOUN
bracis-19081	60	19	of	of	ADP
bracis-19081	60	20	each	each	DET
bracis-19081	60	21	iteration	iteration	NOUN
bracis-19081	60	22	of	of	ADP
bracis-19081	60	23	the	the	DET
bracis-19081	60	24	asl	asl	PROPN
bracis-19081	60	25	algorithm	algorithm	NOUN
bracis-19081	60	26	.	.	PUNCT
bracis-19081	61	1	we	we	PRON
bracis-19081	61	2	expect	expect	VERB
bracis-19081	61	3	these	these	DET
bracis-19081	61	4	two	two	NUM
bracis-19081	61	5	changes	change	NOUN
bracis-19081	61	6	to	to	PART
bracis-19081	61	7	reduce	reduce	VERB
bracis-19081	61	8	the	the	DET
bracis-19081	61	9	risk	risk	NOUN
bracis-19081	61	10	of	of	ADP
bracis-19081	61	11	adding	add	VERB
bracis-19081	61	12	permanent	permanent	ADJ
bracis-19081	61	13	bias	bias	NOUN
bracis-19081	61	14	to	to	ADP
bracis-19081	61	15	both	both	CCONJ
bracis-19081	61	16	the	the	DET
bracis-19081	61	17	trained	train	VERB
bracis-19081	61	18	model	model	NOUN
bracis-19081	61	19	and	and	CCONJ
bracis-19081	61	20	the	the	DET
bracis-19081	61	21	labeled	label	VERB
bracis-19081	61	22	sets	set	NOUN
bracis-19081	61	23	.	.	PUNCT
bracis-19081	62	1	the	the	DET
bracis-19081	62	2	proposed	propose	VERB
bracis-19081	62	3	algorithm	algorithm	NOUN
bracis-19081	62	4	can	can	AUX
bracis-19081	62	5	be	be	AUX
bracis-19081	62	6	thought	think	VERB
bracis-19081	62	7	as	as	ADP
bracis-19081	62	8	an	an	DET
bracis-19081	62	9	iterative	iterative	NOUN
bracis-19081	62	10	semi	semi	ADJ
bracis-19081	62	11	-	-	ADJ
bracis-19081	62	12	supervised	supervised	ADJ
bracis-19081	62	13	learning	learning	NOUN
bracis-19081	62	14	process	process	NOUN
bracis-19081	62	15	,	,	PUNCT
bracis-19081	62	16	as	as	ADP
bracis-19081	62	17	for	for	ADP
bracis-19081	62	18	each	each	DET
bracis-19081	62	19	iteration	iteration	NOUN
bracis-19081	62	20	it	it	PRON
bracis-19081	62	21	identifies	identify	VERB
bracis-19081	62	22	a	a	DET
bracis-19081	62	23	set	set	NOUN
bracis-19081	62	24	of	of	ADP
bracis-19081	62	25	unlabeled	unlabeled	ADJ
bracis-19081	62	26	samples	sample	NOUN
bracis-19081	62	27	that	that	PRON
bracis-19081	62	28	can	can	AUX
bracis-19081	62	29	be	be	AUX
bracis-19081	62	30	reliably	reliably	ADV
bracis-19081	62	31	used	use	VERB
bracis-19081	62	32	for	for	ADP
bracis-19081	62	33	self	self	NOUN
bracis-19081	62	34	-	-	PUNCT
bracis-19081	62	35	training	training	NOUN
bracis-19081	62	36	,	,	PUNCT
bracis-19081	62	37	an	an	DET
bracis-19081	62	38	approach	approach	NOUN
bracis-19081	62	39	that	that	PRON
bracis-19081	62	40	resembles	resemble	VERB
bracis-19081	62	41	current	current	ADJ
bracis-19081	62	42	semi	semi	ADJ
bracis-19081	62	43	-	-	ADJ
bracis-19081	62	44	supervised	supervised	ADJ
bracis-19081	62	45	works	work	NOUN
bracis-19081	62	46	from	from	ADP
bracis-19081	62	47	the	the	DET
bracis-19081	62	48	literature	literature	NOUN
bracis-19081	63	1	[	[	X
bracis-19081	63	2	1	1	NUM
bracis-19081	63	3	]	]	PUNCT
bracis-19081	63	4	.	.	PUNCT
bracis-19081	64	1	figure	figure	NOUN
bracis-19081	64	2	 	 	SPACE
bracis-19081	64	3	1	1	NUM
bracis-19081	64	4	presents	present	VERB
bracis-19081	64	5	a	a	DET
bracis-19081	64	6	comparison	comparison	NOUN
bracis-19081	64	7	between	between	ADP
bracis-19081	64	8	the	the	DET
bracis-19081	64	9	labeling	labeling	NOUN
bracis-19081	64	10	process	process	NOUN
bracis-19081	64	11	and	and	CCONJ
bracis-19081	64	12	training	training	NOUN
bracis-19081	64	13	of	of	ADP
bracis-19081	64	14	the	the	DET
bracis-19081	64	15	model	model	NOUN
bracis-19081	64	16	by	by	ADP
bracis-19081	64	17	the	the	DET
bracis-19081	64	18	asl	asl	PROPN
bracis-19081	64	19	algorithms	algorithm	NOUN
bracis-19081	64	20	presented	present	VERB
bracis-19081	64	21	in	in	ADP
bracis-19081	64	22	the	the	DET
bracis-19081	64	23	literature	literature	NOUN
bracis-19081	64	24	and	and	CCONJ
bracis-19081	64	25	the	the	DET
bracis-19081	64	26	one	one	NOUN
bracis-19081	64	27	proposed	propose	VERB
bracis-19081	64	28	here	here	ADV
bracis-19081	64	29	.	.	PUNCT
bracis-19081	65	1	algorithm	algorithm	NOUN
bracis-19081	65	2	 	 	SPACE
bracis-19081	65	3	1	1	NUM
bracis-19081	65	4	presents	present	VERB
bracis-19081	65	5	a	a	DET
bracis-19081	65	6	more	more	ADV
bracis-19081	65	7	detailed	detailed	ADJ
bracis-19081	65	8	explanation	explanation	NOUN
bracis-19081	65	9	of	of	ADP
bracis-19081	65	10	the	the	DET
bracis-19081	65	11	proposed	propose	VERB
bracis-19081	65	12	active	active	ADJ
bracis-19081	65	13	-	-	PUNCT
bracis-19081	65	14	self	self	NOUN
bracis-19081	65	15	learning	learn	VERB
bracis-19081	65	16	algorithm	algorithm	NOUN
bracis-19081	65	17	.	.	PUNCT
bracis-19081	66	1	fig	fig	NOUN
bracis-19081	66	2	.	.	PUNCT
bracis-19081	67	1	1	1	X
bracis-19081	67	2	.	.	X
bracis-19081	67	3	in	in	ADP
bracis-19081	67	4	the	the	DET
bracis-19081	67	5	diagrams	diagram	NOUN
bracis-19081	67	6	,	,	PUNCT
bracis-19081	67	7	u	u	NOUN
bracis-19081	67	8	and	and	CCONJ
bracis-19081	67	9	l	l	NOUN
bracis-19081	67	10	represent	represent	VERB
bracis-19081	67	11	the	the	DET
bracis-19081	67	12	unlabeled	unlabeled	ADJ
bracis-19081	67	13	and	and	CCONJ
bracis-19081	67	14	labeled	label	VERB
bracis-19081	67	15	sets	set	NOUN
bracis-19081	67	16	,	,	PUNCT
bracis-19081	67	17	respectively	respectively	ADV
bracis-19081	67	18	.	.	PUNCT
bracis-19081	68	1	a.l	a.l	PROPN
bracis-19081	68	2	.	.	PROPN
bracis-19081	68	3	is	be	AUX
bracis-19081	68	4	the	the	DET
bracis-19081	68	5	active	active	ADJ
bracis-19081	68	6	labeled	label	VERB
bracis-19081	68	7	set	set	NOUN
bracis-19081	68	8	,	,	PUNCT
bracis-19081	68	9	which	which	PRON
bracis-19081	68	10	contains	contain	VERB
bracis-19081	68	11	samples	sample	NOUN
bracis-19081	68	12	labeled	label	VERB
bracis-19081	68	13	by	by	ADP
bracis-19081	68	14	the	the	DET
bracis-19081	68	15	oracle	oracle	NOUN
bracis-19081	68	16	.	.	PUNCT
bracis-19081	69	1	s.l	s.l	PROPN
bracis-19081	69	2	.	.	PROPN
bracis-19081	69	3	stands	stand	VERB
bracis-19081	69	4	for	for	ADP
bracis-19081	69	5	self	self	NOUN
bracis-19081	69	6	-	-	PUNCT
bracis-19081	69	7	labeled	label	VERB
bracis-19081	69	8	,	,	PUNCT
bracis-19081	69	9	meaning	mean	VERB
bracis-19081	69	10	the	the	DET
bracis-19081	69	11	set	set	NOUN
bracis-19081	69	12	containing	contain	VERB
bracis-19081	69	13	the	the	DET
bracis-19081	69	14	samples	sample	NOUN
bracis-19081	69	15	labeled	label	VERB
bracis-19081	69	16	by	by	ADP
bracis-19081	69	17	the	the	DET
bracis-19081	69	18	trained	train	VERB
bracis-19081	69	19	model	model	NOUN
bracis-19081	69	20	.	.	PUNCT
bracis-19081	70	1	figure	figure	NOUN
bracis-19081	70	2	(	(	PUNCT
bracis-19081	70	3	a	a	PRON
bracis-19081	70	4	)	)	PUNCT
bracis-19081	70	5	presents	present	VERB
bracis-19081	70	6	the	the	DET
bracis-19081	70	7	asl	asl	PROPN
bracis-19081	70	8	algorithm	algorithm	NOUN
bracis-19081	70	9	found	find	VERB
bracis-19081	70	10	in	in	ADP
bracis-19081	70	11	the	the	DET
bracis-19081	70	12	literature	literature	NOUN
bracis-19081	70	13	,	,	PUNCT
bracis-19081	70	14	where	where	SCONJ
bracis-19081	70	15	both	both	CCONJ
bracis-19081	70	16	the	the	DET
bracis-19081	70	17	oracle	oracle	NOUN
bracis-19081	70	18	and	and	CCONJ
bracis-19081	70	19	the	the	DET
bracis-19081	70	20	trained	train	VERB
bracis-19081	70	21	model	model	NOUN
bracis-19081	70	22	cooperatively	cooperatively	ADV
bracis-19081	70	23	annotate	annotate	VERB
bracis-19081	70	24	unlabeled	unlabeled	ADJ
bracis-19081	70	25	samples	sample	NOUN
bracis-19081	70	26	and	and	CCONJ
bracis-19081	70	27	add	add	VERB
bracis-19081	70	28	them	they	PRON
bracis-19081	70	29	to	to	ADP
bracis-19081	70	30	the	the	DET
bracis-19081	70	31	same	same	ADJ
bracis-19081	70	32	labeled	label	VERB
bracis-19081	70	33	set	set	NOUN
bracis-19081	70	34	,	,	PUNCT
bracis-19081	70	35	which	which	PRON
bracis-19081	70	36	is	be	AUX
bracis-19081	70	37	then	then	ADV
bracis-19081	70	38	used	use	VERB
bracis-19081	70	39	to	to	PART
bracis-19081	70	40	train	train	VERB
bracis-19081	70	41	the	the	DET
bracis-19081	70	42	machine	machine	NOUN
bracis-19081	70	43	learning	learn	VERB
bracis-19081	70	44	model	model	NOUN
bracis-19081	70	45	.	.	PUNCT
bracis-19081	71	1	figure	figure	NOUN
bracis-19081	71	2	(	(	PUNCT
bracis-19081	71	3	b	b	NOUN
bracis-19081	71	4	)	)	PUNCT
bracis-19081	71	5	shows	show	VERB
bracis-19081	71	6	the	the	DET
bracis-19081	71	7	proposed	propose	VERB
bracis-19081	71	8	asl	asl	NOUN
bracis-19081	71	9	algorithm	algorithm	NOUN
bracis-19081	71	10	,	,	PUNCT
bracis-19081	71	11	where	where	SCONJ
bracis-19081	71	12	samples	sample	NOUN
bracis-19081	71	13	labeled	label	VERB
bracis-19081	71	14	by	by	ADP
bracis-19081	71	15	the	the	DET
bracis-19081	71	16	oracle	oracle	NOUN
bracis-19081	71	17	and	and	CCONJ
bracis-19081	71	18	by	by	ADP
bracis-19081	71	19	the	the	DET
bracis-19081	71	20	trained	train	VERB
bracis-19081	71	21	model	model	NOUN
bracis-19081	71	22	are	be	AUX
bracis-19081	71	23	separated	separate	VERB
bracis-19081	71	24	into	into	ADP
bracis-19081	71	25	different	different	ADJ
bracis-19081	71	26	labeled	label	VERB
bracis-19081	71	27	sets	set	NOUN
bracis-19081	71	28	,	,	PUNCT
bracis-19081	71	29	which	which	PRON
bracis-19081	71	30	are	be	AUX
bracis-19081	71	31	used	use	VERB
bracis-19081	71	32	for	for	ADP
bracis-19081	71	33	further	further	ADJ
bracis-19081	71	34	training	training	NOUN
bracis-19081	71	35	of	of	ADP
bracis-19081	71	36	the	the	DET
bracis-19081	71	37	model	model	NOUN
bracis-19081	71	38	,	,	PUNCT
bracis-19081	71	39	but	but	CCONJ
bracis-19081	71	40	with	with	ADP
bracis-19081	71	41	the	the	DET
bracis-19081	71	42	self	self	NOUN
bracis-19081	71	43	-	-	PUNCT
bracis-19081	71	44	labeled	label	VERB
bracis-19081	71	45	set	set	NOUN
bracis-19081	71	46	having	have	VERB
bracis-19081	71	47	a	a	DET
bracis-19081	71	48	lesser	less	ADJ
bracis-19081	71	49	impact	impact	NOUN
bracis-19081	71	50	on	on	ADP
bracis-19081	71	51	the	the	DET
bracis-19081	71	52	model	model	NOUN
bracis-19081	71	53	’s	’s	PART
bracis-19081	71	54	parameters	parameter	NOUN
bracis-19081	71	55	during	during	ADP
bracis-19081	71	56	training	training	NOUN
bracis-19081	71	57	.	.	PUNCT
bracis-19081	72	1	it	it	PRON
bracis-19081	72	2	also	also	ADV
bracis-19081	72	3	shows	show	VERB
bracis-19081	72	4	that	that	SCONJ
bracis-19081	72	5	after	after	ADP
bracis-19081	72	6	training	training	NOUN
bracis-19081	72	7	,	,	PUNCT
bracis-19081	72	8	all	all	DET
bracis-19081	72	9	samples	sample	NOUN
bracis-19081	72	10	labeled	label	VERB
bracis-19081	72	11	by	by	ADP
bracis-19081	72	12	the	the	DET
bracis-19081	72	13	model	model	NOUN
bracis-19081	72	14	are	be	AUX
bracis-19081	72	15	returned	return	VERB
bracis-19081	72	16	to	to	ADP
bracis-19081	72	17	the	the	DET
bracis-19081	72	18	unlabeled	unlabele	VERB
bracis-19081	72	19	set	set	NOUN
bracis-19081	72	20	,	,	PUNCT
bracis-19081	72	21	thus	thus	ADV
bracis-19081	72	22	reducing	reduce	VERB
bracis-19081	72	23	the	the	DET
bracis-19081	72	24	risk	risk	NOUN
bracis-19081	72	25	of	of	ADP
bracis-19081	72	26	introducing	introduce	VERB
bracis-19081	72	27	permanent	permanent	ADJ
bracis-19081	72	28	bias	bias	NOUN
bracis-19081	72	29	to	to	ADP
bracis-19081	72	30	the	the	DET
bracis-19081	72	31	model	model	NOUN
bracis-19081	72	32	throughout	throughout	ADP
bracis-19081	72	33	the	the	DET
bracis-19081	72	34	asl	asl	NOUN
bracis-19081	72	35	process	process	NOUN
bracis-19081	72	36	.	.	PUNCT
bracis-19081	73	1	full	full	ADJ
bracis-19081	73	2	size	size	NOUN
bracis-19081	73	3	image	image	NOUN
bracis-19081	73	4	note	note	VERB
bracis-19081	73	5	that	that	SCONJ
bracis-19081	73	6	in	in	ADP
bracis-19081	73	7	the	the	DET
bracis-19081	73	8	algorithm	algorithm	NOUN
bracis-19081	73	9	 	 	SPACE
bracis-19081	73	10	1	1	NUM
bracis-19081	73	11	,	,	PUNCT
bracis-19081	73	12	m	m	VERB
bracis-19081	73	13	represents	represent	VERB
bracis-19081	73	14	the	the	DET
bracis-19081	73	15	machine	machine	NOUN
bracis-19081	73	16	learning	learning	NOUN
bracis-19081	73	17	model	model	NOUN
bracis-19081	73	18	,	,	PUNCT
bracis-19081	73	19	q	q	PROPN
bracis-19081	73	20	is	be	AUX
bracis-19081	73	21	the	the	DET
bracis-19081	73	22	query	query	NOUN
bracis-19081	73	23	budget	budget	NOUN
bracis-19081	73	24	,	,	PUNCT
bracis-19081	73	25	\(min\_confidence\	\(min\_confidence\	PROPN
bracis-19081	73	26	)	)	PUNCT
bracis-19081	73	27	is	be	AUX
bracis-19081	73	28	the	the	DET
bracis-19081	73	29	minimum	minimum	ADJ
bracis-19081	73	30	confidence	confidence	NOUN
bracis-19081	73	31	the	the	DET
bracis-19081	73	32	model	model	NOUN
bracis-19081	73	33	must	must	AUX
bracis-19081	73	34	have	have	VERB
bracis-19081	73	35	to	to	PART
bracis-19081	73	36	annotate	annotate	VERB
bracis-19081	73	37	an	an	DET
bracis-19081	73	38	unlabeled	unlabeled	ADJ
bracis-19081	73	39	sample	sample	NOUN
bracis-19081	73	40	,	,	PUNCT
bracis-19081	73	41	a.l	a.l	PROPN
bracis-19081	73	42	.	.	PROPN
bracis-19081	73	43	stands	stand	VERB
bracis-19081	73	44	for	for	ADP
bracis-19081	73	45	active	active	ADJ
bracis-19081	73	46	labeled	label	VERB
bracis-19081	73	47	set	set	NOUN
bracis-19081	73	48	which	which	PRON
bracis-19081	73	49	contains	contain	VERB
bracis-19081	73	50	samples	sample	NOUN
bracis-19081	73	51	annotated	annotate	VERB
bracis-19081	73	52	by	by	ADP
bracis-19081	73	53	the	the	DET
bracis-19081	73	54	oracle	oracle	NOUN
bracis-19081	73	55	,	,	PUNCT
bracis-19081	73	56	s.l	s.l	PROPN
bracis-19081	73	57	.	.	PROPN
bracis-19081	73	58	contains	contain	VERB
bracis-19081	73	59	the	the	DET
bracis-19081	73	60	samples	sample	NOUN
bracis-19081	73	61	labeled	label	VERB
bracis-19081	73	62	by	by	ADP
bracis-19081	73	63	the	the	DET
bracis-19081	73	64	trained	train	VERB
bracis-19081	73	65	model	model	NOUN
bracis-19081	73	66	,	,	PUNCT
bracis-19081	73	67	and	and	CCONJ
bracis-19081	73	68	u	u	NOUN
bracis-19081	73	69	represents	represent	VERB
bracis-19081	73	70	the	the	DET
bracis-19081	73	71	set	set	NOUN
bracis-19081	73	72	of	of	ADP
bracis-19081	73	73	unlabeled	unlabeled	ADJ
bracis-19081	73	74	data	datum	NOUN
bracis-19081	73	75	.	.	PUNCT
bracis-19081	74	1	the	the	DET
bracis-19081	74	2	active	active	ADJ
bracis-19081	74	3	learning	learning	NOUN
bracis-19081	74	4	procedure	procedure	NOUN
bracis-19081	74	5	,	,	PUNCT
bracis-19081	74	6	represented	represent	VERB
bracis-19081	74	7	by	by	ADP
bracis-19081	74	8	the	the	DET
bracis-19081	74	9	\(active\_learning\_query(\cdot	\(active\_learning\_query(\cdot	NOUN
bracis-19081	74	10	)	)	PUNCT
bracis-19081	74	11	\	\	ADJ
bracis-19081	74	12	)	)	PUNCT
bracis-19081	74	13	function	function	NOUN
bracis-19081	74	14	in	in	ADP
bracis-19081	74	15	algorithm	algorithm	NOUN
bracis-19081	74	16	 	 	SPACE
bracis-19081	74	17	1	1	NUM
bracis-19081	74	18	,	,	PUNCT
bracis-19081	74	19	identifies	identify	VERB
bracis-19081	74	20	the	the	DET
bracis-19081	74	21	most	most	ADV
bracis-19081	74	22	informative	informative	ADJ
bracis-19081	74	23	unlabeled	unlabele	VERB
bracis-19081	74	24	samples	sample	NOUN
bracis-19081	74	25	to	to	PART
bracis-19081	74	26	be	be	AUX
bracis-19081	74	27	annotated	annotate	VERB
bracis-19081	74	28	by	by	ADP
bracis-19081	74	29	the	the	DET
bracis-19081	74	30	oracle	oracle	NOUN
bracis-19081	74	31	.	.	PUNCT
bracis-19081	75	1	for	for	ADP
bracis-19081	75	2	this	this	DET
bracis-19081	75	3	work	work	NOUN
bracis-19081	75	4	we	we	PRON
bracis-19081	75	5	selected	select	VERB
bracis-19081	75	6	the	the	DET
bracis-19081	75	7	maximum	maximum	NOUN
bracis-19081	75	8	normalized	normalize	VERB
bracis-19081	75	9	log	log	NOUN
bracis-19081	75	10	-	-	PUNCT
bracis-19081	75	11	probability	probability	NOUN
bracis-19081	75	12	(	(	PUNCT
bracis-19081	75	13	mnlp	mnlp	ADJ
bracis-19081	75	14	)	)	PUNCT
bracis-19081	76	1	[	[	X
bracis-19081	76	2	15	15	NUM
bracis-19081	76	3	]	]	PUNCT
bracis-19081	76	4	as	as	ADP
bracis-19081	76	5	the	the	DET
bracis-19081	76	6	sampling	sample	VERB
bracis-19081	76	7	function	function	NOUN
bracis-19081	76	8	,	,	PUNCT
bracis-19081	76	9	as	as	SCONJ
bracis-19081	76	10	it	it	PRON
bracis-19081	76	11	was	be	AUX
bracis-19081	76	12	shown	show	VERB
bracis-19081	76	13	to	to	PART
bracis-19081	76	14	be	be	AUX
bracis-19081	76	15	competitive	competitive	ADJ
bracis-19081	76	16	with	with	ADP
bracis-19081	76	17	more	more	ADV
bracis-19081	76	18	sophisticated	sophisticated	ADJ
bracis-19081	76	19	sampling	sampling	NOUN
bracis-19081	76	20	techniques	technique	NOUN
bracis-19081	76	21	[	[	X
bracis-19081	76	22	16	16	NUM
bracis-19081	76	23	]	]	PUNCT
bracis-19081	76	24	while	while	SCONJ
bracis-19081	76	25	being	be	AUX
bracis-19081	76	26	less	less	ADV
bracis-19081	76	27	expensive	expensive	ADJ
bracis-19081	76	28	to	to	PART
bracis-19081	76	29	be	be	AUX
bracis-19081	76	30	computed	compute	VERB
bracis-19081	76	31	.	.	PUNCT
bracis-19081	77	1	the	the	DET
bracis-19081	77	2	mnlp	mnlp	NOUN
bracis-19081	77	3	of	of	ADP
bracis-19081	77	4	a	a	DET
bracis-19081	77	5	sequence	sequence	NOUN
bracis-19081	77	6	x	x	PUNCT
bracis-19081	77	7	of	of	ADP
bracis-19081	77	8	length	length	NOUN
bracis-19081	77	9	n	n	NUM
bracis-19081	77	10	can	can	AUX
bracis-19081	77	11	be	be	AUX
bracis-19081	77	12	computed	compute	VERB
bracis-19081	77	13	as	as	ADP
bracis-19081	77	14	:	:	PUNCT
bracis-19081	77	15	$	$	SYM
bracis-19081	77	16	$	$	SYM
bracis-19081	77	17	\begin{aligned	\begin{aligne	VERB
bracis-19081	77	18	}	}	PUNCT
bracis-19081	77	19	mnlp(x	mnlp(x	PROPN
bracis-19081	77	20	)	)	PUNCT
bracis-19081	77	21	=	=	NOUN
bracis-19081	78	1	\max	\max	PROPN
bracis-19081	78	2	_	_	PUNCT
bracis-19081	78	3	{	{	PUNCT
bracis-19081	78	4	y_1	y_1	PROPN
bracis-19081	78	5	,	,	PUNCT
bracis-19081	78	6	...	...	PUNCT
bracis-19081	78	7	,	,	PUNCT
bracis-19081	78	8	y_{n-1}}\frac{1}{n}\sum	y_{n-1}}\frac{1}{n}\sum	PROPN
bracis-19081	78	9	^n_{i=0}log\	^n_{i=0}log\	NOUN
bracis-19081	78	10	p(y_i\vert	p(y_i\vert	PROPN
bracis-19081	78	11	x_i	x_i	PROPN
bracis-19081	78	12	,	,	PUNCT
bracis-19081	78	13	y_0	y_0	PROPN
bracis-19081	78	14	,	,	PUNCT
bracis-19081	78	15	y_1	y_1	PROPN
bracis-19081	78	16	,	,	PUNCT
bracis-19081	78	17	...	...	PUNCT
bracis-19081	78	18	,	,	PUNCT
bracis-19081	78	19	y_{i-1	y_{i-1	NUM
bracis-19081	78	20	}	}	PUNCT
bracis-19081	78	21	)	)	PUNCT
bracis-19081	78	22	.	.	PUNCT
bracis-19081	79	1	\end{aligned}$$	\end{aligned}$$	PROPN
bracis-19081	79	2	(	(	PUNCT
bracis-19081	79	3	1	1	NUM
bracis-19081	79	4	)	)	PUNCT
bracis-19081	79	5	for	for	ADP
bracis-19081	79	6	the	the	DET
bracis-19081	79	7	experiments	experiment	NOUN
bracis-19081	79	8	,	,	PUNCT
bracis-19081	79	9	we	we	PRON
bracis-19081	79	10	follow	follow	VERB
bracis-19081	79	11	previous	previous	ADJ
bracis-19081	79	12	works	work	NOUN
bracis-19081	79	13	from	from	ADP
bracis-19081	79	14	the	the	DET
bracis-19081	79	15	literature	literature	NOUN
bracis-19081	79	16	[	[	X
bracis-19081	79	17	16	16	NUM
bracis-19081	79	18	]	]	PUNCT
bracis-19081	79	19	and	and	CCONJ
bracis-19081	79	20	define	define	VERB
bracis-19081	79	21	a	a	DET
bracis-19081	79	22	query	query	NOUN
bracis-19081	79	23	budget	budget	NOUN
bracis-19081	79	24	as	as	SCONJ
bracis-19081	79	25	the	the	DET
bracis-19081	79	26	number	number	NOUN
bracis-19081	79	27	of	of	ADP
bracis-19081	79	28	tokens	token	NOUN
bracis-19081	79	29	that	that	PRON
bracis-19081	79	30	can	can	AUX
bracis-19081	79	31	be	be	AUX
bracis-19081	79	32	selected	select	VERB
bracis-19081	79	33	by	by	ADP
bracis-19081	79	34	the	the	DET
bracis-19081	79	35	sampling	sample	VERB
bracis-19081	79	36	function	function	NOUN
bracis-19081	79	37	to	to	PART
bracis-19081	79	38	be	be	AUX
bracis-19081	79	39	manually	manually	ADV
bracis-19081	79	40	annotated	annotate	VERB
bracis-19081	79	41	by	by	ADP
bracis-19081	79	42	the	the	DET
bracis-19081	79	43	human	human	ADJ
bracis-19081	79	44	annotator	annotator	NOUN
bracis-19081	79	45	in	in	ADP
bracis-19081	79	46	a	a	DET
bracis-19081	79	47	single	single	ADJ
bracis-19081	79	48	iteration	iteration	NOUN
bracis-19081	79	49	of	of	ADP
bracis-19081	79	50	the	the	DET
bracis-19081	79	51	active	active	ADJ
bracis-19081	79	52	learning	learning	NOUN
bracis-19081	79	53	process	process	NOUN
bracis-19081	79	54	.	.	PUNCT
bracis-19081	80	1	we	we	PRON
bracis-19081	80	2	chose	choose	VERB
bracis-19081	80	3	a	a	DET
bracis-19081	80	4	query	query	NOUN
bracis-19081	80	5	budget	budget	NOUN
bracis-19081	80	6	of	of	ADP
bracis-19081	80	7	approximately	approximately	ADV
bracis-19081	80	8	2	2	NUM
bracis-19081	80	9	%	%	NOUN
bracis-19081	80	10	of	of	ADP
bracis-19081	80	11	the	the	DET
bracis-19081	80	12	tokens	token	NOUN
bracis-19081	80	13	from	from	ADP
bracis-19081	80	14	the	the	DET
bracis-19081	80	15	whole	whole	ADJ
bracis-19081	80	16	training	training	NOUN
bracis-19081	80	17	set	set	NOUN
bracis-19081	80	18	.	.	PUNCT
bracis-19081	81	1	thus	thus	ADV
bracis-19081	81	2	,	,	PUNCT
bracis-19081	81	3	the	the	DET
bracis-19081	81	4	query	query	NOUN
bracis-19081	81	5	budget	budget	NOUN
bracis-19081	81	6	was	be	AUX
bracis-19081	81	7	20,000	20,000	NUM
bracis-19081	81	8	,	,	PUNCT
bracis-19081	81	9	6,000	6,000	NUM
bracis-19081	81	10	and	and	CCONJ
bracis-19081	81	11	4,000	4,000	NUM
bracis-19081	81	12	words	word	NOUN
bracis-19081	81	13	for	for	ADP
bracis-19081	81	14	the	the	DET
bracis-19081	81	15	datasets	dataset	NOUN
bracis-19081	81	16	ontonotes5.0	ontonotes5.0	PROPN
bracis-19081	81	17	,	,	PUNCT
bracis-19081	81	18	aposentadoria	aposentadoria	PROPN
bracis-19081	81	19	,	,	PUNCT
bracis-19081	81	20	and	and	CCONJ
bracis-19081	81	21	conll	conll	PROPN
bracis-19081	81	22	2003	2003	NUM
bracis-19081	81	23	,	,	PUNCT
bracis-19081	81	24	respectively	respectively	ADV
bracis-19081	81	25	.	.	PUNCT
bracis-19081	82	1	the	the	DET
bracis-19081	82	2	\(self\_learning\_query(\cdot	\(self\_learning\_query(\cdot	NOUN
bracis-19081	82	3	)	)	PUNCT
bracis-19081	82	4	\	\	NOUN
bracis-19081	82	5	)	)	PUNCT
bracis-19081	82	6	function	function	NOUN
bracis-19081	82	7	in	in	ADP
bracis-19081	82	8	algorithm	algorithm	NOUN
bracis-19081	82	9	 	 	SPACE
bracis-19081	82	10	1	1	NUM
bracis-19081	82	11	identifies	identify	VERB
bracis-19081	82	12	the	the	DET
bracis-19081	82	13	samples	sample	NOUN
bracis-19081	82	14	for	for	ADP
bracis-19081	82	15	which	which	PRON
bracis-19081	82	16	the	the	DET
bracis-19081	82	17	current	current	ADJ
bracis-19081	82	18	trained	train	VERB
bracis-19081	82	19	model	model	NOUN
bracis-19081	82	20	has	have	VERB
bracis-19081	82	21	a	a	DET
bracis-19081	82	22	confidence	confidence	NOUN
bracis-19081	82	23	higher	high	ADJ
bracis-19081	82	24	than	than	ADP
bracis-19081	82	25	a	a	DET
bracis-19081	82	26	predefined	predefine	VERB
bracis-19081	82	27	threshold	threshold	NOUN
bracis-19081	82	28	.	.	PUNCT
bracis-19081	83	1	these	these	DET
bracis-19081	83	2	samples	sample	NOUN
bracis-19081	83	3	are	be	AUX
bracis-19081	83	4	considered	consider	VERB
bracis-19081	83	5	to	to	PART
bracis-19081	83	6	be	be	AUX
bracis-19081	83	7	reliable	reliable	ADJ
bracis-19081	83	8	and	and	CCONJ
bracis-19081	83	9	,	,	PUNCT
bracis-19081	83	10	therefore	therefore	ADV
bracis-19081	83	11	,	,	PUNCT
bracis-19081	83	12	can	can	AUX
bracis-19081	83	13	be	be	AUX
bracis-19081	83	14	used	use	VERB
bracis-19081	83	15	for	for	ADP
bracis-19081	83	16	self	self	NOUN
bracis-19081	83	17	-	-	PUNCT
bracis-19081	83	18	training	training	NOUN
bracis-19081	83	19	.	.	PUNCT
bracis-19081	84	1	a	a	DET
bracis-19081	84	2	minimum	minimum	ADJ
bracis-19081	84	3	confidence	confidence	NOUN
bracis-19081	84	4	of	of	ADP
bracis-19081	84	5	0.99	0.99	NUM
bracis-19081	84	6	was	be	AUX
bracis-19081	84	7	selected	select	VERB
bracis-19081	84	8	in	in	ADP
bracis-19081	84	9	this	this	DET
bracis-19081	84	10	work	work	NOUN
bracis-19081	84	11	as	as	ADP
bracis-19081	84	12	the	the	DET
bracis-19081	84	13	threshold	threshold	NOUN
bracis-19081	84	14	,	,	PUNCT
bracis-19081	84	15	based	base	VERB
bracis-19081	84	16	on	on	ADP
bracis-19081	84	17	experiments	experiment	NOUN
bracis-19081	84	18	performed	perform	VERB
bracis-19081	84	19	using	use	VERB
bracis-19081	84	20	the	the	DET
bracis-19081	84	21	validation	validation	NOUN
bracis-19081	84	22	set	set	NOUN
bracis-19081	84	23	.	.	PUNCT
bracis-19081	85	1	the	the	DET
bracis-19081	85	2	learning	learning	NOUN
bracis-19081	85	3	rate	rate	NOUN
bracis-19081	85	4	for	for	ADP
bracis-19081	85	5	training	train	VERB
bracis-19081	85	6	the	the	DET
bracis-19081	85	7	model	model	NOUN
bracis-19081	85	8	with	with	ADP
bracis-19081	85	9	self	self	NOUN
bracis-19081	85	10	-	-	PUNCT
bracis-19081	85	11	labeled	label	VERB
bracis-19081	85	12	samples	sample	NOUN
bracis-19081	85	13	is	be	AUX
bracis-19081	85	14	one	one	NUM
bracis-19081	85	15	tenth	tenth	NOUN
bracis-19081	85	16	of	of	ADP
bracis-19081	85	17	the	the	DET
bracis-19081	85	18	learning	learning	NOUN
bracis-19081	85	19	rate	rate	NOUN
bracis-19081	85	20	used	use	VERB
bracis-19081	85	21	for	for	ADP
bracis-19081	85	22	training	training	NOUN
bracis-19081	85	23	with	with	ADP
bracis-19081	85	24	the	the	DET
bracis-19081	85	25	active	active	ADV
bracis-19081	85	26	-	-	PUNCT
bracis-19081	85	27	labeled	label	VERB
bracis-19081	85	28	samples	sample	NOUN
bracis-19081	85	29	,	,	PUNCT
bracis-19081	85	30	with	with	ADP
bracis-19081	85	31	this	this	DET
bracis-19081	85	32	value	value	NOUN
bracis-19081	85	33	being	be	AUX
bracis-19081	85	34	selected	select	VERB
bracis-19081	85	35	from	from	ADP
bracis-19081	85	36	initial	initial	ADJ
bracis-19081	85	37	experiments	experiment	NOUN
bracis-19081	85	38	using	use	VERB
bracis-19081	85	39	the	the	DET
bracis-19081	85	40	validation	validation	NOUN
bracis-19081	85	41	set	set	NOUN
bracis-19081	85	42	.	.	PUNCT
bracis-19081	86	1	for	for	ADP
bracis-19081	86	2	the	the	DET
bracis-19081	86	3	model	model	NOUN
bracis-19081	86	4	training	training	NOUN
bracis-19081	86	5	,	,	PUNCT
bracis-19081	86	6	represented	represent	VERB
bracis-19081	86	7	as	as	ADP
bracis-19081	86	8	\(train\_model(\cdot	\(train\_model(\cdot	ADJ
bracis-19081	86	9	)	)	PUNCT
bracis-19081	86	10	\	\	NOUN
bracis-19081	86	11	)	)	PUNCT
bracis-19081	86	12	in	in	ADP
bracis-19081	86	13	algorithm	algorithm	NOUN
bracis-19081	86	14	1	1	NUM
bracis-19081	86	15	,	,	PUNCT
bracis-19081	86	16	we	we	PRON
bracis-19081	86	17	used	use	VERB
bracis-19081	86	18	classic	classic	ADJ
bracis-19081	86	19	supervised	supervised	ADJ
bracis-19081	86	20	training	training	NOUN
bracis-19081	86	21	.	.	PUNCT
bracis-19081	87	1	the	the	DET
bracis-19081	87	2	single	single	ADJ
bracis-19081	87	3	difference	difference	NOUN
bracis-19081	87	4	is	be	AUX
bracis-19081	87	5	that	that	SCONJ
bracis-19081	87	6	during	during	ADP
bracis-19081	87	7	training	training	NOUN
bracis-19081	87	8	,	,	PUNCT
bracis-19081	87	9	we	we	PRON
bracis-19081	87	10	alternate	alternate	VERB
bracis-19081	87	11	using	use	VERB
bracis-19081	87	12	minibatches	minibatche	NOUN
bracis-19081	87	13	from	from	ADP
bracis-19081	87	14	the	the	DET
bracis-19081	87	15	a.l	a.l	PROPN
bracis-19081	87	16	.	.	PROPN
bracis-19081	88	1	and	and	CCONJ
bracis-19081	88	2	s.l	s.l	PROPN
bracis-19081	88	3	.	.	PROPN
bracis-19081	88	4	sets	set	NOUN
bracis-19081	88	5	.	.	PUNCT
bracis-19081	89	1	2.2	2.2	NUM
bracis-19081	89	2	dynamic	dynamic	ADJ
bracis-19081	89	3	update	update	NOUN
bracis-19081	89	4	of	of	ADP
bracis-19081	89	5	 	 	SPACE
bracis-19081	89	6	training	training	NOUN
bracis-19081	89	7	epochs	epoch	NOUN
bracis-19081	89	8	dute	dute	NOUN
bracis-19081	89	9	inspired	inspire	VERB
bracis-19081	89	10	by	by	ADP
bracis-19081	89	11	the	the	DET
bracis-19081	89	12	overall	overall	ADJ
bracis-19081	89	13	uncertainty	uncertainty	NOUN
bracis-19081	89	14	stopping	stop	VERB
bracis-19081	89	15	criterion	criterion	NOUN
bracis-19081	89	16	for	for	ADP
bracis-19081	89	17	active	active	ADJ
bracis-19081	89	18	learning	learning	NOUN
bracis-19081	89	19	algorithms	algorithm	NOUN
bracis-19081	89	20	,	,	PUNCT
bracis-19081	89	21	proposed	propose	VERB
bracis-19081	89	22	by	by	ADP
bracis-19081	89	23	zhu	zhu	PROPN
bracis-19081	89	24	et	et	PROPN
bracis-19081	89	25	al	al	PROPN
bracis-19081	89	26	.	.	PUNCT
bracis-19081	90	1	[	[	X
bracis-19081	90	2	18	18	NUM
bracis-19081	90	3	]	]	PUNCT
bracis-19081	90	4	,	,	PUNCT
bracis-19081	90	5	we	we	PRON
bracis-19081	90	6	propose	propose	VERB
bracis-19081	90	7	the	the	DET
bracis-19081	90	8	dynamic	dynamic	ADJ
bracis-19081	90	9	update	update	NOUN
bracis-19081	90	10	of	of	ADP
bracis-19081	90	11	training	training	NOUN
bracis-19081	90	12	epochs	epoch	NOUN
bracis-19081	90	13	(	(	PUNCT
bracis-19081	90	14	dute	dute	PROPN
bracis-19081	90	15	)	)	PUNCT
bracis-19081	90	16	,	,	PUNCT
bracis-19081	90	17	an	an	DET
bracis-19081	90	18	early	early	ADJ
bracis-19081	90	19	stopping	stopping	NOUN
bracis-19081	90	20	strategy	strategy	NOUN
bracis-19081	90	21	that	that	PRON
bracis-19081	90	22	reduces	reduce	VERB
bracis-19081	90	23	the	the	DET
bracis-19081	90	24	number	number	NOUN
bracis-19081	90	25	of	of	ADP
bracis-19081	90	26	training	training	NOUN
bracis-19081	90	27	epochs	epoch	NOUN
bracis-19081	90	28	based	base	VERB
bracis-19081	90	29	on	on	ADP
bracis-19081	90	30	the	the	DET
bracis-19081	90	31	mean	mean	ADJ
bracis-19081	90	32	confidence	confidence	NOUN
bracis-19081	90	33	of	of	ADP
bracis-19081	90	34	the	the	DET
bracis-19081	90	35	trained	train	VERB
bracis-19081	90	36	model	model	NOUN
bracis-19081	90	37	on	on	ADP
bracis-19081	90	38	its	its	PRON
bracis-19081	90	39	predictions	prediction	NOUN
bracis-19081	90	40	for	for	ADP
bracis-19081	90	41	the	the	DET
bracis-19081	90	42	unlabeled	unlabele	VERB
bracis-19081	90	43	set	set	NOUN
bracis-19081	90	44	.	.	PUNCT
bracis-19081	91	1	we	we	PRON
bracis-19081	91	2	hypothesize	hypothesize	VERB
bracis-19081	91	3	that	that	SCONJ
bracis-19081	91	4	the	the	DET
bracis-19081	91	5	model	model	NOUN
bracis-19081	91	6	’s	’s	PART
bracis-19081	91	7	mean	mean	ADJ
bracis-19081	91	8	confidence	confidence	NOUN
bracis-19081	91	9	indicates	indicate	VERB
bracis-19081	91	10	how	how	SCONJ
bracis-19081	91	11	well	well	ADV
bracis-19081	91	12	the	the	DET
bracis-19081	91	13	labeled	label	VERB
bracis-19081	91	14	set	set	NOUN
bracis-19081	91	15	represents	represent	VERB
bracis-19081	91	16	the	the	DET
bracis-19081	91	17	whole	whole	ADJ
bracis-19081	91	18	dataset	dataset	NOUN
bracis-19081	91	19	,	,	PUNCT
bracis-19081	91	20	meaning	mean	VERB
bracis-19081	91	21	that	that	SCONJ
bracis-19081	91	22	adding	add	VERB
bracis-19081	91	23	more	more	ADJ
bracis-19081	91	24	unlabeled	unlabeled	ADJ
bracis-19081	91	25	samples	sample	NOUN
bracis-19081	91	26	to	to	ADP
bracis-19081	91	27	the	the	DET
bracis-19081	91	28	labeled	label	VERB
bracis-19081	91	29	set	set	NOUN
bracis-19081	91	30	incurs	incur	VERB
bracis-19081	91	31	in	in	ADP
bracis-19081	91	32	little	little	ADJ
bracis-19081	91	33	change	change	NOUN
bracis-19081	91	34	of	of	ADP
bracis-19081	91	35	the	the	DET
bracis-19081	91	36	labeled	label	VERB
bracis-19081	91	37	set	set	NOUN
bracis-19081	91	38	’s	’s	PART
bracis-19081	91	39	label	label	NOUN
bracis-19081	91	40	distribution	distribution	NOUN
bracis-19081	91	41	.	.	PUNCT
bracis-19081	92	1	because	because	SCONJ
bracis-19081	92	2	of	of	ADP
bracis-19081	92	3	that	that	PRON
bracis-19081	92	4	,	,	PUNCT
bracis-19081	92	5	we	we	PRON
bracis-19081	92	6	argue	argue	VERB
bracis-19081	92	7	that	that	SCONJ
bracis-19081	92	8	fewer	few	ADJ
bracis-19081	92	9	training	training	NOUN
bracis-19081	92	10	epochs	epoch	NOUN
bracis-19081	92	11	are	be	AUX
bracis-19081	92	12	required	require	VERB
bracis-19081	92	13	as	as	ADP
bracis-19081	92	14	the	the	DET
bracis-19081	92	15	model	model	NOUN
bracis-19081	92	16	’s	’s	PART
bracis-19081	92	17	confidence	confidence	NOUN
bracis-19081	92	18	on	on	ADP
bracis-19081	92	19	the	the	DET
bracis-19081	92	20	unlabeled	unlabele	VERB
bracis-19081	92	21	set	set	NOUN
bracis-19081	92	22	increases	increase	NOUN
bracis-19081	92	23	.	.	PUNCT
bracis-19081	93	1	to	to	PART
bracis-19081	93	2	measure	measure	VERB
bracis-19081	93	3	the	the	DET
bracis-19081	93	4	model	model	NOUN
bracis-19081	93	5	’s	’s	PART
bracis-19081	93	6	confidence	confidence	NOUN
bracis-19081	93	7	on	on	ADP
bracis-19081	93	8	the	the	DET
bracis-19081	93	9	unlabeled	unlabele	VERB
bracis-19081	93	10	set	set	NOUN
bracis-19081	93	11	,	,	PUNCT
bracis-19081	93	12	we	we	PRON
bracis-19081	93	13	propose	propose	VERB
bracis-19081	93	14	to	to	PART
bracis-19081	93	15	use	use	VERB
bracis-19081	93	16	the	the	DET
bracis-19081	93	17	harmonic	harmonic	ADJ
bracis-19081	93	18	mean	mean	NOUN
bracis-19081	93	19	of	of	ADP
bracis-19081	93	20	the	the	DET
bracis-19081	93	21	model	model	NOUN
bracis-19081	93	22	’s	’s	PART
bracis-19081	93	23	normalized	normalize	VERB
bracis-19081	93	24	confidence	confidence	NOUN
bracis-19081	93	25	for	for	ADP
bracis-19081	93	26	each	each	DET
bracis-19081	93	27	unlabeled	unlabeled	ADJ
bracis-19081	93	28	sample	sample	NOUN
bracis-19081	93	29	.	.	PUNCT
bracis-19081	94	1	the	the	DET
bracis-19081	94	2	harmonic	harmonic	ADJ
bracis-19081	94	3	mean	mean	NOUN
bracis-19081	94	4	was	be	AUX
bracis-19081	94	5	used	use	VERB
bracis-19081	94	6	to	to	PART
bracis-19081	94	7	emphasize	emphasize	VERB
bracis-19081	94	8	those	those	DET
bracis-19081	94	9	unlabeled	unlabeled	ADJ
bracis-19081	94	10	samples	sample	NOUN
bracis-19081	94	11	for	for	ADP
bracis-19081	94	12	which	which	PRON
bracis-19081	94	13	the	the	DET
bracis-19081	94	14	trained	train	VERB
bracis-19081	94	15	model	model	NOUN
bracis-19081	94	16	has	have	VERB
bracis-19081	94	17	lower	low	ADJ
bracis-19081	94	18	confidence	confidence	NOUN
bracis-19081	94	19	in	in	ADP
bracis-19081	94	20	its	its	PRON
bracis-19081	94	21	predictions	prediction	NOUN
bracis-19081	94	22	.	.	PUNCT
bracis-19081	95	1	the	the	DET
bracis-19081	95	2	normalized	normalize	VERB
bracis-19081	95	3	confidence	confidence	NOUN
bracis-19081	95	4	of	of	ADP
bracis-19081	95	5	a	a	DET
bracis-19081	95	6	sequence	sequence	NOUN
bracis-19081	95	7	of	of	ADP
bracis-19081	95	8	elements	element	NOUN
bracis-19081	95	9	x	x	PUNCT
bracis-19081	95	10	can	can	AUX
bracis-19081	95	11	be	be	AUX
bracis-19081	95	12	computed	compute	VERB
bracis-19081	95	13	as	as	ADP
bracis-19081	95	14	$	$	SYM
bracis-19081	95	15	$	$	SYM
bracis-19081	95	16	\begin{aligned	\begin{aligne	VERB
bracis-19081	95	17	}	}	PUNCT
bracis-19081	95	18	nc(x	nc(x	NUM
bracis-19081	95	19	)	)	PUNCT
bracis-19081	95	20	=	=	SYM
bracis-19081	95	21	e^{mnlp(x	e^{mnlp(x	ADJ
bracis-19081	95	22	)	)	PUNCT
bracis-19081	95	23	}	}	PUNCT
bracis-19081	95	24	,	,	PUNCT
bracis-19081	95	25	\end{aligned}$$	\end{aligned}$$	X
bracis-19081	95	26	(	(	PUNCT
bracis-19081	95	27	2	2	NUM
bracis-19081	95	28	)	)	PUNCT
bracis-19081	95	29	where	where	SCONJ
bracis-19081	95	30	mnlp	mnlp	X
bracis-19081	95	31	(	(	PUNCT
bracis-19081	95	32	.	.	PUNCT
bracis-19081	95	33	)	)	PUNCT
bracis-19081	95	34	is	be	AUX
bracis-19081	95	35	the	the	DET
bracis-19081	95	36	maximum	maximum	ADJ
bracis-19081	95	37	normalized	normalize	VERB
bracis-19081	95	38	log	log	NOUN
bracis-19081	95	39	-	-	PUNCT
bracis-19081	95	40	probability	probability	NOUN
bracis-19081	95	41	,	,	PUNCT
bracis-19081	95	42	presented	present	VERB
bracis-19081	95	43	in	in	ADP
bracis-19081	95	44	eq	eq	ADP
bracis-19081	95	45	.	.	PUNCT
bracis-19081	95	46	 	 	SPACE
bracis-19081	96	1	1	1	NUM
bracis-19081	96	2	.	.	PUNCT
bracis-19081	97	1	the	the	DET
bracis-19081	97	2	harmonic	harmonic	ADJ
bracis-19081	97	3	mean	mean	NOUN
bracis-19081	97	4	for	for	SCONJ
bracis-19081	97	5	the	the	DET
bracis-19081	97	6	model	model	NOUN
bracis-19081	97	7	’s	’s	PART
bracis-19081	97	8	confidence	confidence	NOUN
bracis-19081	97	9	on	on	ADP
bracis-19081	97	10	the	the	DET
bracis-19081	97	11	unlabeled	unlabele	VERB
bracis-19081	97	12	set	set	NOUN
bracis-19081	97	13	u	u	NOUN
bracis-19081	97	14	is	be	AUX
bracis-19081	97	15	computed	compute	VERB
bracis-19081	97	16	as	as	ADP
bracis-19081	97	17	(	(	PUNCT
bracis-19081	97	18	3	3	NUM
bracis-19081	97	19	)	)	PUNCT
bracis-19081	97	20	given	give	VERB
bracis-19081	97	21	the	the	DET
bracis-19081	97	22	mean	mean	ADJ
bracis-19081	97	23	confidence	confidence	NOUN
bracis-19081	97	24	of	of	ADP
bracis-19081	97	25	the	the	DET
bracis-19081	97	26	trained	train	VERB
bracis-19081	97	27	model	model	NOUN
bracis-19081	97	28	on	on	ADP
bracis-19081	97	29	the	the	DET
bracis-19081	97	30	unlabeled	unlabele	VERB
bracis-19081	97	31	set	set	NOUN
bracis-19081	97	32	,	,	PUNCT
bracis-19081	97	33	the	the	DET
bracis-19081	97	34	dute	dute	NOUN
bracis-19081	97	35	strategy	strategy	NOUN
bracis-19081	97	36	computes	compute	VERB
bracis-19081	97	37	the	the	DET
bracis-19081	97	38	number	number	NOUN
bracis-19081	97	39	of	of	ADP
bracis-19081	97	40	training	training	NOUN
bracis-19081	97	41	epochs	epoch	NOUN
bracis-19081	97	42	to	to	PART
bracis-19081	97	43	be	be	AUX
bracis-19081	97	44	used	use	VERB
bracis-19081	97	45	at	at	ADP
bracis-19081	97	46	the	the	DET
bracis-19081	97	47	k	k	PROPN
bracis-19081	97	48	-	-	PUNCT
bracis-19081	97	49	th	th	VERB
bracis-19081	97	50	iteration	iteration	NOUN
bracis-19081	97	51	of	of	ADP
bracis-19081	97	52	the	the	DET
bracis-19081	97	53	active	active	ADJ
bracis-19081	97	54	learning	learning	NOUN
bracis-19081	97	55	algorithm	algorithm	NOUN
bracis-19081	97	56	,	,	PUNCT
bracis-19081	97	57	as	as	SCONJ
bracis-19081	97	58	presented	present	VERB
bracis-19081	97	59	in	in	ADP
bracis-19081	97	60	eq	eq	ADP
bracis-19081	97	61	.	.	PUNCT
bracis-19081	97	62	 	 	SPACE
bracis-19081	97	63	4	4	NUM
bracis-19081	97	64	.	.	PUNCT
bracis-19081	97	65	$	$	SYM
bracis-19081	97	66	$	$	SYM
bracis-19081	97	67	\begin{aligned	\begin{aligne	VERB
bracis-19081	97	68	}	}	PUNCT
bracis-19081	97	69	\begin{aligned	\begin{aligne	VERB
bracis-19081	97	70	}	}	PUNCT
bracis-19081	97	71	epoch(k	epoch(k	NOUN
bracis-19081	97	72	)	)	PUNCT
bracis-19081	97	73	=	=	PROPN
bracis-19081	97	74	&	&	CCONJ
bracis-19081	97	75	round\bigg	round\bigg	PRON
bracis-19081	98	1	[	[	X
bracis-19081	98	2	(	(	PUNCT
bracis-19081	98	3	1.0	1.0	NUM
bracis-19081	98	4	momentum	momentum	NOUN
bracis-19081	98	5	)	)	PUNCT
bracis-19081	98	6	\times	\times	ADP
bracis-19081	98	7	(	(	PUNCT
bracis-19081	98	8	1.0	1.0	NUM
bracis-19081	98	9	mc(u	mc(u	NUM
bracis-19081	98	10	)	)	PUNCT
bracis-19081	98	11	)	)	PUNCT
bracis-19081	98	12	\times	\times	ADP
bracis-19081	98	13	epoch(k-1	epoch(k-1	NOUN
bracis-19081	98	14	)	)	PUNCT
bracis-19081	98	15	\\	\\	NOUN
bracis-19081	98	16	+	+	ADJ
bracis-19081	98	17	\&(momentum	\&(momentum	PROPN
bracis-19081	98	18	)	)	PUNCT
bracis-19081	98	19	\times	\times	ADP
bracis-19081	98	20	epoch(k-1)\bigg	epoch(k-1)\bigg	PRON
bracis-19081	98	21	]	]	PUNCT
bracis-19081	98	22	\end{aligned	\end{aligne	VERB
bracis-19081	98	23	}	}	PUNCT
bracis-19081	98	24	\end{aligned}$$	\end{aligned}$$	X
bracis-19081	98	25	(	(	PUNCT
bracis-19081	98	26	4	4	NUM
bracis-19081	98	27	)	)	PUNCT
bracis-19081	98	28	in	in	ADP
bracis-19081	98	29	this	this	DET
bracis-19081	98	30	work	work	NOUN
bracis-19081	98	31	,	,	PUNCT
bracis-19081	98	32	a	a	DET
bracis-19081	98	33	momentum	momentum	NOUN
bracis-19081	98	34	of	of	ADP
bracis-19081	98	35	0.9	0.9	NUM
bracis-19081	98	36	was	be	AUX
bracis-19081	98	37	selected	select	VERB
bracis-19081	98	38	based	base	VERB
bracis-19081	98	39	on	on	ADP
bracis-19081	98	40	initial	initial	ADJ
bracis-19081	98	41	experiments	experiment	NOUN
bracis-19081	98	42	performed	perform	VERB
bracis-19081	98	43	using	use	VERB
bracis-19081	98	44	the	the	DET
bracis-19081	98	45	validation	validation	NOUN
bracis-19081	98	46	sets	set	NOUN
bracis-19081	98	47	of	of	ADP
bracis-19081	98	48	the	the	DET
bracis-19081	98	49	datasets	dataset	NOUN
bracis-19081	98	50	presented	present	VERB
bracis-19081	98	51	in	in	ADP
bracis-19081	98	52	sect	sect	NOUN
bracis-19081	98	53	.	.	PUNCT
bracis-19081	98	54	 	 	SPACE
bracis-19081	99	1	2.3	2.3	NUM
bracis-19081	99	2	.	.	PUNCT
bracis-19081	100	1	2.3	2.3	NUM
bracis-19081	100	2	experiments	experiment	NOUN
bracis-19081	100	3	this	this	DET
bracis-19081	100	4	section	section	NOUN
bracis-19081	100	5	describes	describe	VERB
bracis-19081	100	6	the	the	DET
bracis-19081	100	7	experiments	experiment	NOUN
bracis-19081	100	8	designed	design	VERB
bracis-19081	100	9	in	in	ADP
bracis-19081	100	10	order	order	NOUN
bracis-19081	100	11	to	to	PART
bracis-19081	100	12	validate	validate	VERB
bracis-19081	100	13	the	the	DET
bracis-19081	100	14	proposed	propose	VERB
bracis-19081	100	15	asl	asl	NOUN
bracis-19081	100	16	algorithm	algorithm	PROPN
bracis-19081	100	17	and	and	CCONJ
bracis-19081	100	18	dute	dute	NOUN
bracis-19081	100	19	strategy	strategy	NOUN
bracis-19081	100	20	.	.	PUNCT
bracis-19081	101	1	this	this	DET
bracis-19081	101	2	validation	validation	NOUN
bracis-19081	101	3	was	be	AUX
bracis-19081	101	4	done	do	VERB
bracis-19081	101	5	in	in	ADP
bracis-19081	101	6	two	two	NUM
bracis-19081	101	7	separate	separate	ADJ
bracis-19081	101	8	experiments	experiment	NOUN
bracis-19081	101	9	.	.	PUNCT
bracis-19081	102	1	the	the	DET
bracis-19081	102	2	first	first	ADJ
bracis-19081	102	3	experiment	experiment	NOUN
bracis-19081	102	4	compares	compare	VERB
bracis-19081	102	5	the	the	DET
bracis-19081	102	6	proposed	propose	VERB
bracis-19081	102	7	asl	asl	NOUN
bracis-19081	102	8	algorithm	algorithm	NOUN
bracis-19081	102	9	with	with	ADP
bracis-19081	102	10	the	the	DET
bracis-19081	102	11	dute	dute	NOUN
bracis-19081	102	12	strategy	strategy	NOUN
bracis-19081	102	13	to	to	ADP
bracis-19081	102	14	the	the	DET
bracis-19081	102	15	al	al	PROPN
bracis-19081	102	16	algorithm	algorithm	PROPN
bracis-19081	102	17	proposed	propose	VERB
bracis-19081	102	18	by	by	ADP
bracis-19081	102	19	shen	shen	PROPN
bracis-19081	102	20	et	et	PROPN
bracis-19081	102	21	al	al	PROPN
bracis-19081	102	22	.	.	PUNCT
bracis-19081	103	1	the	the	DET
bracis-19081	103	2	second	second	ADJ
bracis-19081	103	3	experiment	experiment	NOUN
bracis-19081	103	4	is	be	AUX
bracis-19081	103	5	an	an	DET
bracis-19081	103	6	ablation	ablation	NOUN
bracis-19081	103	7	study	study	NOUN
bracis-19081	103	8	,	,	PUNCT
bracis-19081	103	9	where	where	SCONJ
bracis-19081	103	10	we	we	PRON
bracis-19081	103	11	investigate	investigate	VERB
bracis-19081	103	12	the	the	DET
bracis-19081	103	13	impact	impact	NOUN
bracis-19081	103	14	that	that	PRON
bracis-19081	103	15	the	the	DET
bracis-19081	103	16	dute	dute	NOUN
bracis-19081	103	17	strategy	strategy	NOUN
bracis-19081	103	18	has	have	VERB
bracis-19081	103	19	on	on	ADP
bracis-19081	103	20	both	both	CCONJ
bracis-19081	103	21	the	the	DET
bracis-19081	103	22	execution	execution	NOUN
bracis-19081	103	23	time	time	NOUN
bracis-19081	103	24	of	of	ADP
bracis-19081	103	25	the	the	DET
bracis-19081	103	26	algorithm	algorithm	NOUN
bracis-19081	103	27	and	and	CCONJ
bracis-19081	103	28	the	the	DET
bracis-19081	103	29	trained	train	VERB
bracis-19081	103	30	model	model	NOUN
bracis-19081	103	31	’s	’s	PART
bracis-19081	103	32	performance	performance	NOUN
bracis-19081	103	33	.	.	PUNCT
bracis-19081	104	1	the	the	DET
bracis-19081	104	2	ner	ner	NOUN
bracis-19081	104	3	datasets	dataset	NOUN
bracis-19081	104	4	,	,	PUNCT
bracis-19081	104	5	neural	neural	ADJ
bracis-19081	104	6	models	model	NOUN
bracis-19081	104	7	and	and	CCONJ
bracis-19081	104	8	baselines	baseline	NOUN
bracis-19081	104	9	used	use	VERB
bracis-19081	104	10	on	on	ADP
bracis-19081	104	11	both	both	DET
bracis-19081	104	12	experiments	experiment	NOUN
bracis-19081	104	13	are	be	AUX
bracis-19081	104	14	presented	present	VERB
bracis-19081	104	15	in	in	ADP
bracis-19081	104	16	the	the	DET
bracis-19081	104	17	following	follow	VERB
bracis-19081	104	18	sections	section	NOUN
bracis-19081	104	19	.	.	PUNCT
bracis-19081	105	1	datasets	dataset	NOUN
bracis-19081	105	2	for	for	ADP
bracis-19081	105	3	the	the	DET
bracis-19081	105	4	experiments	experiment	NOUN
bracis-19081	105	5	,	,	PUNCT
bracis-19081	105	6	we	we	PRON
bracis-19081	105	7	used	use	VERB
bracis-19081	105	8	two	two	NUM
bracis-19081	105	9	english	english	ADJ
bracis-19081	105	10	ner	ner	NOUN
bracis-19081	105	11	datasets	dataset	NOUN
bracis-19081	105	12	frequently	frequently	ADV
bracis-19081	105	13	used	use	VERB
bracis-19081	105	14	in	in	ADP
bracis-19081	105	15	the	the	DET
bracis-19081	105	16	literature	literature	NOUN
bracis-19081	105	17	,	,	PUNCT
bracis-19081	105	18	namely	namely	ADV
bracis-19081	105	19	the	the	DET
bracis-19081	105	20	ontonotes	ontonote	NOUN
bracis-19081	105	21	5.0	5.0	NUM
bracis-19081	106	1	[	[	SYM
bracis-19081	106	2	11	11	NUM
bracis-19081	106	3	]	]	PUNCT
bracis-19081	106	4	and	and	CCONJ
bracis-19081	106	5	the	the	DET
bracis-19081	106	6	conll	conll	NOUN
bracis-19081	106	7	2003	2003	NUM
bracis-19081	107	1	[	[	X
bracis-19081	107	2	13	13	NUM
bracis-19081	107	3	]	]	PUNCT
bracis-19081	107	4	.	.	PUNCT
bracis-19081	108	1	additionally	additionally	ADV
bracis-19081	108	2	,	,	PUNCT
bracis-19081	108	3	we	we	PRON
bracis-19081	108	4	also	also	ADV
bracis-19081	108	5	experimented	experiment	VERB
bracis-19081	108	6	on	on	ADP
bracis-19081	108	7	a	a	DET
bracis-19081	108	8	novel	novel	ADJ
bracis-19081	108	9	legal	legal	ADJ
bracis-19081	108	10	domain	domain	NOUN
bracis-19081	108	11	ner	ner	NOUN
bracis-19081	108	12	dataset	dataset	VERB
bracis-19081	108	13	in	in	ADP
bracis-19081	108	14	portuguese	portuguese	PROPN
bracis-19081	108	15	,	,	PUNCT
bracis-19081	108	16	named	name	VERB
bracis-19081	108	17	aposentadoria	aposentadoria	PROPN
bracis-19081	108	18	(	(	PUNCT
bracis-19081	108	19	retirement	retirement	NOUN
bracis-19081	108	20	,	,	PUNCT
bracis-19081	108	21	in	in	ADP
bracis-19081	108	22	direct	direct	ADJ
bracis-19081	108	23	translation	translation	NOUN
bracis-19081	108	24	)	)	PUNCT
bracis-19081	108	25	dataset	dataset	NOUN
bracis-19081	108	26	.	.	PUNCT
bracis-19081	109	1	the	the	DET
bracis-19081	109	2	aposentadoria	aposentadoria	PROPN
bracis-19081	109	3	dataset	dataset	NOUN
bracis-19081	109	4	contains	contain	VERB
bracis-19081	109	5	named	name	VERB
bracis-19081	109	6	entities	entity	NOUN
bracis-19081	109	7	from	from	ADP
bracis-19081	109	8	10	10	NUM
bracis-19081	109	9	distinct	distinct	ADJ
bracis-19081	109	10	classes	class	NOUN
bracis-19081	109	11	related	relate	VERB
bracis-19081	109	12	to	to	ADP
bracis-19081	109	13	retirement	retirement	NOUN
bracis-19081	109	14	acts	act	NOUN
bracis-19081	109	15	of	of	ADP
bracis-19081	109	16	public	public	ADJ
bracis-19081	109	17	employees	employee	NOUN
bracis-19081	109	18	published	publish	VERB
bracis-19081	109	19	in	in	ADP
bracis-19081	109	20	the	the	DET
bracis-19081	109	21	diário	diário	PROPN
bracis-19081	109	22	oficial	oficial	NOUN
bracis-19081	109	23	do	do	VERB
bracis-19081	109	24	distrito	distrito	PROPN
bracis-19081	109	25	federal	federal	PROPN
bracis-19081	109	26	(	(	PUNCT
bracis-19081	109	27	brazilian	brazilian	ADJ
bracis-19081	109	28	federal	federal	ADJ
bracis-19081	109	29	district	district	PROPN
bracis-19081	109	30	official	official	ADJ
bracis-19081	109	31	gazette	gazette	PROPN
bracis-19081	109	32	,	,	PUNCT
bracis-19081	109	33	in	in	ADP
bracis-19081	109	34	direct	direct	ADJ
bracis-19081	109	35	translation	translation	NOUN
bracis-19081	109	36	)	)	PUNCT
bracis-19081	109	37	.	.	PUNCT
bracis-19081	110	1	it	it	PRON
bracis-19081	110	2	’s	’	VERB
bracis-19081	110	3	a	a	DET
bracis-19081	110	4	part	part	NOUN
bracis-19081	110	5	of	of	ADP
bracis-19081	110	6	a	a	DET
bracis-19081	110	7	major	major	ADJ
bracis-19081	110	8	dataset	dataset	NOUN
bracis-19081	110	9	created	create	VERB
bracis-19081	110	10	by	by	ADP
bracis-19081	110	11	collaborators	collaborator	NOUN
bracis-19081	110	12	of	of	ADP
bracis-19081	110	13	project	project	NOUN
bracis-19081	110	14	knedlefootnote	knedlefootnote	VERB
bracis-19081	110	15	1	1	NUM
bracis-19081	110	16	.	.	PUNCT
bracis-19081	111	1	more	more	ADJ
bracis-19081	111	2	information	information	NOUN
bracis-19081	111	3	about	about	ADP
bracis-19081	111	4	the	the	DET
bracis-19081	111	5	dataset	dataset	NOUN
bracis-19081	111	6	as	as	ADV
bracis-19081	111	7	well	well	ADV
bracis-19081	111	8	as	as	ADP
bracis-19081	111	9	a	a	DET
bracis-19081	111	10	download	download	NOUN
bracis-19081	111	11	link	link	NOUN
bracis-19081	111	12	to	to	ADP
bracis-19081	111	13	it	it	PRON
bracis-19081	111	14	are	be	AUX
bracis-19081	111	15	available	available	ADJ
bracis-19081	111	16	at	at	ADP
bracis-19081	111	17	the	the	DET
bracis-19081	111	18	github	github	PROPN
bracis-19081	111	19	repositoryfootnote	repositoryfootnote	VERB
bracis-19081	111	20	2	2	NUM
bracis-19081	111	21	.	.	PUNCT
bracis-19081	111	22	table	table	NOUN
bracis-19081	111	23	 	 	SPACE
bracis-19081	111	24	1	1	NUM
bracis-19081	111	25	presents	present	VERB
bracis-19081	111	26	the	the	DET
bracis-19081	111	27	datasets	dataset	NOUN
bracis-19081	111	28	used	use	VERB
bracis-19081	111	29	in	in	ADP
bracis-19081	111	30	the	the	DET
bracis-19081	111	31	experiments	experiment	NOUN
bracis-19081	111	32	,	,	PUNCT
bracis-19081	111	33	along	along	ADP
bracis-19081	111	34	with	with	ADP
bracis-19081	111	35	relevant	relevant	ADJ
bracis-19081	111	36	information	information	NOUN
bracis-19081	111	37	such	such	ADJ
bracis-19081	111	38	as	as	ADP
bracis-19081	111	39	domain	domain	NOUN
bracis-19081	111	40	area	area	NOUN
bracis-19081	111	41	and	and	CCONJ
bracis-19081	111	42	language	language	NOUN
bracis-19081	111	43	.	.	PUNCT
bracis-19081	112	1	table	table	NOUN
bracis-19081	112	2	1	1	NUM
bracis-19081	112	3	.	.	PUNCT
bracis-19081	113	1	datasets	dataset	NOUN
bracis-19081	113	2	to	to	PART
bracis-19081	113	3	be	be	AUX
bracis-19081	113	4	used	use	VERB
bracis-19081	113	5	for	for	ADP
bracis-19081	113	6	experiments	experiment	NOUN
bracis-19081	113	7	on	on	ADP
bracis-19081	113	8	ner.full	ner.full	NUM
bracis-19081	113	9	size	size	NOUN
bracis-19081	113	10	table	table	NOUN
bracis-19081	113	11	for	for	ADP
bracis-19081	113	12	the	the	DET
bracis-19081	113	13	experiments	experiment	NOUN
bracis-19081	113	14	,	,	PUNCT
bracis-19081	113	15	all	all	DET
bracis-19081	113	16	datasets	dataset	NOUN
bracis-19081	113	17	were	be	AUX
bracis-19081	113	18	preprocessed	preprocesse	VERB
bracis-19081	113	19	by	by	ADP
bracis-19081	113	20	converting	convert	VERB
bracis-19081	113	21	them	they	PRON
bracis-19081	113	22	to	to	ADP
bracis-19081	113	23	the	the	DET
bracis-19081	113	24	iobes	iobe	NOUN
bracis-19081	113	25	notation	notation	NOUN
bracis-19081	113	26	which	which	PRON
bracis-19081	113	27	is	be	AUX
bracis-19081	113	28	frequently	frequently	ADV
bracis-19081	113	29	adopted	adopt	VERB
bracis-19081	113	30	by	by	ADP
bracis-19081	113	31	works	work	NOUN
bracis-19081	113	32	on	on	ADP
bracis-19081	113	33	ner	ner	NOUN
bracis-19081	113	34	in	in	ADP
bracis-19081	113	35	the	the	DET
bracis-19081	113	36	literature	literature	NOUN
bracis-19081	113	37	[	[	X
bracis-19081	113	38	1	1	NUM
bracis-19081	113	39	,	,	PUNCT
bracis-19081	113	40	5	5	NUM
bracis-19081	113	41	,	,	PUNCT
bracis-19081	113	42	7	7	NUM
bracis-19081	113	43	]	]	PUNCT
bracis-19081	113	44	for	for	ADP
bracis-19081	113	45	being	be	AUX
bracis-19081	113	46	capable	capable	ADJ
bracis-19081	113	47	of	of	ADP
bracis-19081	113	48	significantly	significantly	ADV
bracis-19081	113	49	improving	improve	VERB
bracis-19081	113	50	the	the	DET
bracis-19081	113	51	model	model	NOUN
bracis-19081	113	52	’s	’s	PART
bracis-19081	113	53	performance	performance	NOUN
bracis-19081	113	54	[	[	X
bracis-19081	113	55	12	12	NUM
bracis-19081	113	56	]	]	PUNCT
bracis-19081	113	57	.	.	PUNCT
bracis-19081	114	1	also	also	ADV
bracis-19081	114	2	,	,	PUNCT
bracis-19081	114	3	numeric	numeric	ADJ
bracis-19081	114	4	characters	character	NOUN
bracis-19081	114	5	were	be	AUX
bracis-19081	114	6	replaced	replace	VERB
bracis-19081	114	7	by	by	ADP
bracis-19081	114	8	#	#	NOUN
bracis-19081	114	9	and	and	CCONJ
bracis-19081	114	10	0	0	NUM
bracis-19081	114	11	characters	character	NOUN
bracis-19081	114	12	for	for	ADP
bracis-19081	114	13	english	english	ADJ
bracis-19081	114	14	and	and	CCONJ
bracis-19081	114	15	portuguese	portuguese	ADJ
bracis-19081	114	16	datasets	dataset	NOUN
bracis-19081	114	17	,	,	PUNCT
bracis-19081	114	18	respectively	respectively	ADV
bracis-19081	114	19	.	.	PUNCT
bracis-19081	115	1	both	both	DET
bracis-19081	115	2	replacements	replacement	NOUN
bracis-19081	115	3	were	be	AUX
bracis-19081	115	4	made	make	VERB
bracis-19081	115	5	in	in	ADP
bracis-19081	115	6	order	order	NOUN
bracis-19081	115	7	to	to	PART
bracis-19081	115	8	enable	enable	VERB
bracis-19081	115	9	the	the	DET
bracis-19081	115	10	use	use	NOUN
bracis-19081	115	11	of	of	ADP
bracis-19081	115	12	pretrained	pretraine	VERB
bracis-19081	115	13	word	word	NOUN
bracis-19081	115	14	embeddings	embedding	NOUN
bracis-19081	115	15	used	use	VERB
bracis-19081	115	16	by	by	ADP
bracis-19081	115	17	the	the	DET
bracis-19081	115	18	neural	neural	ADJ
bracis-19081	115	19	models	model	NOUN
bracis-19081	115	20	,	,	PUNCT
bracis-19081	115	21	which	which	PRON
bracis-19081	115	22	are	be	AUX
bracis-19081	115	23	better	well	ADV
bracis-19081	115	24	described	describe	VERB
bracis-19081	115	25	next	next	ADV
bracis-19081	115	26	.	.	PUNCT
bracis-19081	116	1	neural	neural	ADJ
bracis-19081	116	2	models	model	NOUN
bracis-19081	116	3	the	the	DET
bracis-19081	116	4	models	model	NOUN
bracis-19081	116	5	to	to	PART
bracis-19081	116	6	be	be	AUX
bracis-19081	116	7	used	use	VERB
bracis-19081	116	8	are	be	AUX
bracis-19081	116	9	those	those	PRON
bracis-19081	116	10	that	that	PRON
bracis-19081	116	11	appear	appear	VERB
bracis-19081	116	12	in	in	ADP
bracis-19081	116	13	the	the	DET
bracis-19081	116	14	work	work	NOUN
bracis-19081	116	15	by	by	ADP
bracis-19081	116	16	siddhant	siddhant	NOUN
bracis-19081	116	17	and	and	CCONJ
bracis-19081	116	18	lipton	lipton	PROPN
bracis-19081	117	1	[	[	X
bracis-19081	117	2	16	16	NUM
bracis-19081	117	3	]	]	X
bracis-19081	117	4	,	,	PUNCT
bracis-19081	117	5	namely	namely	ADV
bracis-19081	117	6	the	the	DET
bracis-19081	117	7	cnn	cnn	PROPN
bracis-19081	117	8	-	-	PUNCT
bracis-19081	117	9	cnn	cnn	PROPN
bracis-19081	117	10	-	-	PUNCT
bracis-19081	117	11	lstm	lstm	NOUN
bracis-19081	117	12	introduced	introduce	VERB
bracis-19081	117	13	by	by	ADP
bracis-19081	117	14	shen	shen	PROPN
bracis-19081	117	15	et	et	PROPN
bracis-19081	117	16	al	al	PROPN
bracis-19081	117	17	.	.	PUNCT
bracis-19081	118	1	[	[	X
bracis-19081	118	2	15	15	NUM
bracis-19081	118	3	]	]	PUNCT
bracis-19081	118	4	and	and	CCONJ
bracis-19081	118	5	the	the	DET
bracis-19081	118	6	cnn	cnn	PROPN
bracis-19081	118	7	-	-	PUNCT
bracis-19081	118	8	bilstm	bilstm	NOUN
bracis-19081	118	9	-	-	PUNCT
bracis-19081	118	10	crf	crf	NOUN
bracis-19081	118	11	designed	design	VERB
bracis-19081	118	12	by	by	ADP
bracis-19081	118	13	ma	ma	PROPN
bracis-19081	118	14	and	and	CCONJ
bracis-19081	118	15	hovy	hovy	VERB
bracis-19081	119	1	[	[	X
bracis-19081	119	2	7	7	NUM
bracis-19081	119	3	]	]	PUNCT
bracis-19081	119	4	.	.	PUNCT
bracis-19081	120	1	the	the	DET
bracis-19081	120	2	hyperparameters	hyperparameter	NOUN
bracis-19081	120	3	used	use	VERB
bracis-19081	120	4	for	for	ADP
bracis-19081	120	5	both	both	DET
bracis-19081	120	6	models	model	NOUN
bracis-19081	120	7	were	be	AUX
bracis-19081	120	8	similar	similar	ADJ
bracis-19081	120	9	to	to	ADP
bracis-19081	120	10	those	those	PRON
bracis-19081	120	11	from	from	ADP
bracis-19081	120	12	their	their	PRON
bracis-19081	120	13	original	original	ADJ
bracis-19081	120	14	papers	paper	NOUN
bracis-19081	120	15	for	for	ADP
bracis-19081	120	16	the	the	DET
bracis-19081	120	17	experiments	experiment	NOUN
bracis-19081	120	18	performed	perform	VERB
bracis-19081	120	19	in	in	ADP
bracis-19081	120	20	the	the	DET
bracis-19081	120	21	english	english	ADJ
bracis-19081	120	22	ner	ner	NOUN
bracis-19081	120	23	datasets	dataset	NOUN
bracis-19081	120	24	,	,	PUNCT
bracis-19081	120	25	and	and	CCONJ
bracis-19081	120	26	a	a	DET
bracis-19081	120	27	grid	grid	NOUN
bracis-19081	120	28	-	-	PUNCT
bracis-19081	120	29	search	search	NOUN
bracis-19081	120	30	was	be	AUX
bracis-19081	120	31	performed	perform	VERB
bracis-19081	120	32	using	use	VERB
bracis-19081	120	33	the	the	DET
bracis-19081	120	34	validation	validation	NOUN
bracis-19081	120	35	set	set	VERB
bracis-19081	120	36	on	on	ADP
bracis-19081	120	37	the	the	DET
bracis-19081	120	38	aposentadoria	aposentadoria	NOUN
bracis-19081	120	39	dataset	dataset	NOUN
bracis-19081	120	40	to	to	PART
bracis-19081	120	41	find	find	VERB
bracis-19081	120	42	the	the	DET
bracis-19081	120	43	best	good	ADJ
bracis-19081	120	44	performing	performing	NOUN
bracis-19081	120	45	parameters	parameter	NOUN
bracis-19081	120	46	for	for	ADP
bracis-19081	120	47	both	both	DET
bracis-19081	120	48	models	model	NOUN
bracis-19081	120	49	.	.	PUNCT
bracis-19081	121	1	the	the	DET
bracis-19081	121	2	parameters	parameter	NOUN
bracis-19081	121	3	for	for	ADP
bracis-19081	121	4	the	the	DET
bracis-19081	121	5	cnn	cnn	PROPN
bracis-19081	121	6	-	-	PUNCT
bracis-19081	121	7	cnn	cnn	PROPN
bracis-19081	121	8	-	-	PUNCT
bracis-19081	121	9	lstm	lstm	PROPN
bracis-19081	121	10	to	to	PART
bracis-19081	121	11	be	be	AUX
bracis-19081	121	12	trained	train	VERB
bracis-19081	121	13	on	on	ADP
bracis-19081	121	14	the	the	DET
bracis-19081	121	15	english	english	ADJ
bracis-19081	121	16	ner	ner	NOUN
bracis-19081	121	17	datasets	dataset	NOUN
bracis-19081	121	18	were	be	AUX
bracis-19081	121	19	similar	similar	ADJ
bracis-19081	121	20	to	to	ADP
bracis-19081	121	21	those	those	PRON
bracis-19081	121	22	presented	present	VERB
bracis-19081	121	23	in	in	ADP
bracis-19081	121	24	the	the	DET
bracis-19081	121	25	experiments	experiment	NOUN
bracis-19081	121	26	of	of	ADP
bracis-19081	121	27	siddhant	siddhant	NOUN
bracis-19081	121	28	and	and	CCONJ
bracis-19081	121	29	lipton	lipton	PROPN
bracis-19081	122	1	[	[	X
bracis-19081	122	2	16	16	NUM
bracis-19081	122	3	]	]	PUNCT
bracis-19081	122	4	,	,	PUNCT
bracis-19081	122	5	where	where	SCONJ
bracis-19081	122	6	the	the	DET
bracis-19081	122	7	character	character	NOUN
bracis-19081	122	8	-	-	PUNCT
bracis-19081	122	9	level	level	NOUN
bracis-19081	122	10	cnn	cnn	PROPN
bracis-19081	122	11	uses	use	VERB
bracis-19081	122	12	25	25	NUM
bracis-19081	122	13	dimensional	dimensional	ADJ
bracis-19081	122	14	character	character	NOUN
bracis-19081	122	15	embeddings	embedding	NOUN
bracis-19081	122	16	,	,	PUNCT
bracis-19081	122	17	the	the	DET
bracis-19081	122	18	1	1	NUM
bracis-19081	122	19	-	-	PUNCT
bracis-19081	122	20	d	d	NOUN
bracis-19081	122	21	convolution	convolution	NOUN
bracis-19081	122	22	layer	layer	NOUN
bracis-19081	122	23	has	have	VERB
bracis-19081	122	24	50	50	NUM
bracis-19081	122	25	filters	filter	NOUN
bracis-19081	122	26	,	,	PUNCT
bracis-19081	122	27	kernel	kernel	NOUN
bracis-19081	122	28	size	size	NOUN
bracis-19081	122	29	of	of	ADP
bracis-19081	122	30	3	3	NUM
bracis-19081	122	31	,	,	PUNCT
bracis-19081	122	32	stride	stride	NOUN
bracis-19081	122	33	and	and	CCONJ
bracis-19081	122	34	padding	padding	NOUN
bracis-19081	122	35	of	of	ADP
bracis-19081	122	36	1	1	NUM
bracis-19081	122	37	.	.	PUNCT
bracis-19081	123	1	the	the	DET
bracis-19081	123	2	word	word	NOUN
bracis-19081	123	3	-	-	PUNCT
bracis-19081	123	4	level	level	NOUN
bracis-19081	123	5	cnn	cnn	PROPN
bracis-19081	123	6	has	have	VERB
bracis-19081	123	7	two	two	NUM
bracis-19081	123	8	blocks	block	NOUN
bracis-19081	123	9	,	,	PUNCT
bracis-19081	123	10	where	where	SCONJ
bracis-19081	123	11	each	each	DET
bracis-19081	123	12	block	block	NOUN
bracis-19081	123	13	has	have	VERB
bracis-19081	123	14	a	a	DET
bracis-19081	123	15	1	1	NUM
bracis-19081	123	16	-	-	PUNCT
bracis-19081	123	17	d	d	NOUN
bracis-19081	123	18	convolutional	convolutional	ADJ
bracis-19081	123	19	layer	layer	NOUN
bracis-19081	123	20	with	with	ADP
bracis-19081	123	21	800	800	NUM
bracis-19081	123	22	filters	filter	NOUN
bracis-19081	123	23	,	,	PUNCT
bracis-19081	123	24	kernel	kernel	NOUN
bracis-19081	123	25	size	size	NOUN
bracis-19081	123	26	of	of	ADP
bracis-19081	123	27	5	5	NUM
bracis-19081	123	28	,	,	PUNCT
bracis-19081	123	29	stride	stride	NOUN
bracis-19081	123	30	of	of	ADP
bracis-19081	123	31	1	1	NUM
bracis-19081	123	32	and	and	CCONJ
bracis-19081	123	33	padding	padding	NOUN
bracis-19081	123	34	of	of	ADP
bracis-19081	123	35	2	2	NUM
bracis-19081	123	36	.	.	PUNCT
bracis-19081	124	1	the	the	DET
bracis-19081	124	2	lstm	lstm	PROPN
bracis-19081	124	3	tag	tag	NOUN
bracis-19081	124	4	decoder	decoder	NOUN
bracis-19081	124	5	consists	consist	VERB
bracis-19081	124	6	of	of	ADP
bracis-19081	124	7	an	an	DET
bracis-19081	124	8	lstm	lstm	ADJ
bracis-19081	124	9	layer	layer	NOUN
bracis-19081	124	10	of	of	ADP
bracis-19081	124	11	size	size	NOUN
bracis-19081	124	12	256	256	NUM
bracis-19081	124	13	.	.	PUNCT
bracis-19081	125	1	all	all	DET
bracis-19081	125	2	dropout	dropout	NOUN
bracis-19081	125	3	layers	layer	NOUN
bracis-19081	125	4	for	for	ADP
bracis-19081	125	5	the	the	DET
bracis-19081	125	6	cnn	cnn	PROPN
bracis-19081	125	7	-	-	PUNCT
bracis-19081	125	8	cnn	cnn	PROPN
bracis-19081	125	9	-	-	PUNCT
bracis-19081	125	10	lstm	lstm	ADJ
bracis-19081	125	11	model	model	NOUN
bracis-19081	125	12	have	have	VERB
bracis-19081	125	13	probability	probability	NOUN
bracis-19081	125	14	0.5	0.5	NUM
bracis-19081	125	15	.	.	PUNCT
bracis-19081	126	1	for	for	SCONJ
bracis-19081	126	2	the	the	DET
bracis-19081	126	3	portuguese	portuguese	ADJ
bracis-19081	126	4	ner	ner	NOUN
bracis-19081	126	5	dataset	dataset	VERB
bracis-19081	126	6	,	,	PUNCT
bracis-19081	126	7	a	a	DET
bracis-19081	126	8	grid	grid	NOUN
bracis-19081	126	9	-	-	PUNCT
bracis-19081	126	10	search	search	NOUN
bracis-19081	126	11	was	be	AUX
bracis-19081	126	12	performed	perform	VERB
bracis-19081	126	13	using	use	VERB
bracis-19081	126	14	the	the	DET
bracis-19081	126	15	validation	validation	NOUN
bracis-19081	126	16	set	set	NOUN
bracis-19081	126	17	and	and	CCONJ
bracis-19081	126	18	the	the	DET
bracis-19081	126	19	final	final	ADJ
bracis-19081	126	20	architecture	architecture	NOUN
bracis-19081	126	21	chosen	choose	VERB
bracis-19081	126	22	had	have	VERB
bracis-19081	126	23	the	the	DET
bracis-19081	126	24	following	following	ADJ
bracis-19081	126	25	hyperparameters	hyperparameter	NOUN
bracis-19081	126	26	:	:	PUNCT
bracis-19081	126	27	the	the	DET
bracis-19081	126	28	character	character	NOUN
bracis-19081	126	29	-	-	PUNCT
bracis-19081	126	30	level	level	NOUN
bracis-19081	126	31	cnn	cnn	PROPN
bracis-19081	126	32	had	have	VERB
bracis-19081	126	33	the	the	DET
bracis-19081	126	34	same	same	ADJ
bracis-19081	126	35	parameters	parameter	NOUN
bracis-19081	126	36	as	as	ADP
bracis-19081	126	37	those	those	PRON
bracis-19081	126	38	used	use	VERB
bracis-19081	126	39	for	for	ADP
bracis-19081	126	40	the	the	DET
bracis-19081	126	41	english	english	ADJ
bracis-19081	126	42	datasets	dataset	NOUN
bracis-19081	126	43	.	.	PUNCT
bracis-19081	127	1	the	the	DET
bracis-19081	127	2	word	word	NOUN
bracis-19081	127	3	-	-	PUNCT
bracis-19081	127	4	level	level	NOUN
bracis-19081	127	5	cnn	cnn	NOUN
bracis-19081	127	6	has	have	VERB
bracis-19081	127	7	one	one	NUM
bracis-19081	127	8	block	block	NOUN
bracis-19081	127	9	,	,	PUNCT
bracis-19081	127	10	consisting	consist	VERB
bracis-19081	127	11	of	of	ADP
bracis-19081	127	12	a	a	DET
bracis-19081	127	13	1	1	NUM
bracis-19081	127	14	-	-	PUNCT
bracis-19081	127	15	d	d	NOUN
bracis-19081	127	16	convolution	convolution	NOUN
bracis-19081	127	17	layer	layer	NOUN
bracis-19081	127	18	with	with	ADP
bracis-19081	127	19	400	400	NUM
bracis-19081	127	20	filters	filter	NOUN
bracis-19081	127	21	,	,	PUNCT
bracis-19081	127	22	kernel	kernel	NOUN
bracis-19081	127	23	size	size	NOUN
bracis-19081	127	24	of	of	ADP
bracis-19081	127	25	5	5	NUM
bracis-19081	127	26	,	,	PUNCT
bracis-19081	127	27	stride	stride	NOUN
bracis-19081	127	28	of	of	ADP
bracis-19081	127	29	1	1	NUM
bracis-19081	127	30	and	and	CCONJ
bracis-19081	127	31	padding	padding	NOUN
bracis-19081	127	32	of	of	ADP
bracis-19081	127	33	2	2	NUM
bracis-19081	127	34	.	.	PUNCT
bracis-19081	128	1	the	the	DET
bracis-19081	128	2	lstm	lstm	PROPN
bracis-19081	128	3	tag	tag	NOUN
bracis-19081	128	4	decoder	decoder	NOUN
bracis-19081	128	5	has	have	AUX
bracis-19081	128	6	size	size	NOUN
bracis-19081	128	7	128	128	NUM
bracis-19081	128	8	.	.	PUNCT
bracis-19081	129	1	all	all	DET
bracis-19081	129	2	dropout	dropout	NOUN
bracis-19081	129	3	probabilities	probability	NOUN
bracis-19081	129	4	are	be	AUX
bracis-19081	129	5	still	still	ADV
bracis-19081	129	6	of	of	ADP
bracis-19081	129	7	0.5	0.5	NUM
bracis-19081	129	8	.	.	PUNCT
bracis-19081	130	1	the	the	DET
bracis-19081	130	2	cnn	cnn	PROPN
bracis-19081	130	3	-	-	PUNCT
bracis-19081	130	4	bilstm	bilstm	NOUN
bracis-19081	130	5	-	-	PUNCT
bracis-19081	130	6	crf	crf	NOUN
bracis-19081	130	7	model	model	NOUN
bracis-19081	130	8	trained	train	VERB
bracis-19081	130	9	on	on	ADP
bracis-19081	130	10	the	the	DET
bracis-19081	130	11	english	english	ADJ
bracis-19081	130	12	ner	ner	NOUN
bracis-19081	130	13	datasets	dataset	NOUN
bracis-19081	130	14	has	have	VERB
bracis-19081	130	15	a	a	DET
bracis-19081	130	16	character	character	NOUN
bracis-19081	130	17	-	-	PUNCT
bracis-19081	130	18	level	level	NOUN
bracis-19081	130	19	cnn	cnn	NOUN
bracis-19081	130	20	with	with	ADP
bracis-19081	130	21	30	30	NUM
bracis-19081	130	22	dimensional	dimensional	ADJ
bracis-19081	130	23	character	character	NOUN
bracis-19081	130	24	embeddings	embedding	NOUN
bracis-19081	130	25	,	,	PUNCT
bracis-19081	130	26	a	a	DET
bracis-19081	130	27	1	1	NUM
bracis-19081	130	28	-	-	PUNCT
bracis-19081	130	29	d	d	NOUN
bracis-19081	130	30	convolution	convolution	NOUN
bracis-19081	130	31	layer	layer	NOUN
bracis-19081	130	32	with	with	ADP
bracis-19081	130	33	30	30	NUM
bracis-19081	130	34	filters	filter	NOUN
bracis-19081	130	35	,	,	PUNCT
bracis-19081	130	36	kernel	kernel	NOUN
bracis-19081	130	37	size	size	NOUN
bracis-19081	130	38	of	of	ADP
bracis-19081	130	39	3	3	NUM
bracis-19081	130	40	,	,	PUNCT
bracis-19081	130	41	padding	padding	NOUN
bracis-19081	130	42	of	of	ADP
bracis-19081	130	43	1	1	NUM
bracis-19081	130	44	and	and	CCONJ
bracis-19081	130	45	stride	stride	NOUN
bracis-19081	130	46	of	of	ADP
bracis-19081	130	47	1	1	NUM
bracis-19081	130	48	.	.	PUNCT
bracis-19081	131	1	the	the	DET
bracis-19081	131	2	bilstm	bilstm	NOUN
bracis-19081	131	3	layer	layer	NOUN
bracis-19081	131	4	has	have	VERB
bracis-19081	131	5	size	size	NOUN
bracis-19081	131	6	300	300	NUM
bracis-19081	131	7	.	.	PUNCT
bracis-19081	132	1	all	all	DET
bracis-19081	132	2	dropout	dropout	NOUN
bracis-19081	132	3	probabilities	probability	NOUN
bracis-19081	132	4	are	be	AUX
bracis-19081	132	5	set	set	VERB
bracis-19081	132	6	to	to	ADP
bracis-19081	132	7	0.5	0.5	NUM
bracis-19081	132	8	.	.	PUNCT
bracis-19081	133	1	for	for	ADP
bracis-19081	133	2	the	the	DET
bracis-19081	133	3	portuguese	portuguese	ADJ
bracis-19081	133	4	dataset	dataset	NOUN
bracis-19081	133	5	,	,	PUNCT
bracis-19081	133	6	a	a	DET
bracis-19081	133	7	grid	grid	NOUN
bracis-19081	133	8	-	-	PUNCT
bracis-19081	133	9	search	search	NOUN
bracis-19081	133	10	was	be	AUX
bracis-19081	133	11	employed	employ	VERB
bracis-19081	133	12	to	to	PART
bracis-19081	133	13	define	define	VERB
bracis-19081	133	14	the	the	DET
bracis-19081	133	15	model	model	NOUN
bracis-19081	133	16	’s	’s	PART
bracis-19081	133	17	best	good	ADJ
bracis-19081	133	18	parameters	parameter	NOUN
bracis-19081	133	19	.	.	PUNCT
bracis-19081	134	1	the	the	DET
bracis-19081	134	2	chosen	choose	VERB
bracis-19081	134	3	model	model	NOUN
bracis-19081	134	4	had	have	VERB
bracis-19081	134	5	the	the	DET
bracis-19081	134	6	same	same	ADJ
bracis-19081	134	7	parameters	parameter	NOUN
bracis-19081	134	8	for	for	ADP
bracis-19081	134	9	the	the	DET
bracis-19081	134	10	character	character	NOUN
bracis-19081	134	11	-	-	PUNCT
bracis-19081	134	12	level	level	NOUN
bracis-19081	134	13	cnn	cnn	NOUN
bracis-19081	134	14	as	as	ADP
bracis-19081	134	15	that	that	PRON
bracis-19081	134	16	used	use	VERB
bracis-19081	134	17	for	for	ADP
bracis-19081	134	18	english	english	ADJ
bracis-19081	134	19	datasets	dataset	NOUN
bracis-19081	134	20	,	,	PUNCT
bracis-19081	134	21	while	while	SCONJ
bracis-19081	134	22	the	the	DET
bracis-19081	134	23	bilstm	bilstm	NOUN
bracis-19081	134	24	layer	layer	NOUN
bracis-19081	134	25	has	have	VERB
bracis-19081	134	26	size	size	NOUN
bracis-19081	134	27	256	256	NUM
bracis-19081	134	28	.	.	PUNCT
bracis-19081	135	1	the	the	DET
bracis-19081	135	2	pretrained	pretraine	VERB
bracis-19081	135	3	embeddings	embedding	NOUN
bracis-19081	135	4	used	use	VERB
bracis-19081	135	5	for	for	ADP
bracis-19081	135	6	both	both	DET
bracis-19081	135	7	models	model	NOUN
bracis-19081	135	8	for	for	ADP
bracis-19081	135	9	the	the	DET
bracis-19081	135	10	english	english	ADJ
bracis-19081	135	11	datasets	dataset	NOUN
bracis-19081	135	12	were	be	AUX
bracis-19081	135	13	the	the	DET
bracis-19081	135	14	glove	glove	NOUN
bracis-19081	135	15	embeddings	embedding	NOUN
bracis-19081	135	16	of	of	ADP
bracis-19081	135	17	100	100	NUM
bracis-19081	135	18	dimensions	dimension	NOUN
bracis-19081	135	19	pretrained	pretraine	VERB
bracis-19081	135	20	on	on	ADP
bracis-19081	135	21	an	an	DET
bracis-19081	135	22	english	english	ADJ
bracis-19081	135	23	newswire	newswire	NOUN
bracis-19081	135	24	corpus	corpus	NOUN
bracis-19081	135	25	[	[	X
bracis-19081	135	26	10	10	NUM
bracis-19081	135	27	]	]	PUNCT
bracis-19081	135	28	.	.	PUNCT
bracis-19081	136	1	for	for	ADP
bracis-19081	136	2	the	the	DET
bracis-19081	136	3	portuguese	portuguese	ADJ
bracis-19081	136	4	dataset	dataset	NOUN
bracis-19081	136	5	,	,	PUNCT
bracis-19081	136	6	the	the	DET
bracis-19081	136	7	glove	glove	NOUN
bracis-19081	136	8	embeddings	embedding	NOUN
bracis-19081	136	9	of	of	ADP
bracis-19081	136	10	300	300	NUM
bracis-19081	136	11	dimensions	dimension	NOUN
bracis-19081	136	12	pretrained	pretraine	VERB
bracis-19081	136	13	on	on	ADP
bracis-19081	136	14	a	a	DET
bracis-19081	136	15	multi	multi	ADJ
bracis-19081	136	16	-	-	ADJ
bracis-19081	136	17	genre	genre	ADJ
bracis-19081	136	18	portuguese	portuguese	ADJ
bracis-19081	136	19	corpus	corpus	NOUN
bracis-19081	136	20	[	[	X
bracis-19081	136	21	2	2	NUM
bracis-19081	136	22	]	]	PUNCT
bracis-19081	136	23	was	be	AUX
bracis-19081	136	24	used	use	VERB
bracis-19081	136	25	.	.	PUNCT
bracis-19081	137	1	for	for	ADP
bracis-19081	137	2	optimization	optimization	NOUN
bracis-19081	137	3	of	of	ADP
bracis-19081	137	4	the	the	DET
bracis-19081	137	5	models	model	NOUN
bracis-19081	137	6	throughout	throughout	ADP
bracis-19081	137	7	training	training	NOUN
bracis-19081	137	8	,	,	PUNCT
bracis-19081	137	9	we	we	PRON
bracis-19081	137	10	used	use	VERB
bracis-19081	137	11	stochastic	stochastic	ADJ
bracis-19081	137	12	gradient	gradient	ADJ
bracis-19081	137	13	descent	descent	NOUN
bracis-19081	137	14	of	of	ADP
bracis-19081	137	15	the	the	DET
bracis-19081	137	16	cross	cross	PROPN
bracis-19081	137	17	entropy	entropy	PROPN
bracis-19081	137	18	loss	loss	NOUN
bracis-19081	137	19	for	for	ADP
bracis-19081	137	20	the	the	DET
bracis-19081	137	21	cnn	cnn	PROPN
bracis-19081	137	22	-	-	PUNCT
bracis-19081	137	23	cnn	cnn	PROPN
bracis-19081	137	24	-	-	PUNCT
bracis-19081	137	25	lstm	lstm	PROPN
bracis-19081	137	26	and	and	CCONJ
bracis-19081	137	27	the	the	DET
bracis-19081	137	28	negative	negative	ADJ
bracis-19081	137	29	log	log	NOUN
bracis-19081	137	30	-	-	PUNCT
bracis-19081	137	31	likelihood	likelihood	NOUN
bracis-19081	137	32	for	for	ADP
bracis-19081	137	33	the	the	DET
bracis-19081	137	34	cnn	cnn	PROPN
bracis-19081	137	35	-	-	PUNCT
bracis-19081	137	36	bilstm	bilstm	NOUN
bracis-19081	137	37	-	-	PUNCT
bracis-19081	137	38	crf	crf	NOUN
bracis-19081	137	39	.	.	PUNCT
bracis-19081	138	1	a	a	DET
bracis-19081	138	2	constant	constant	ADJ
bracis-19081	138	3	momentum	momentum	NOUN
bracis-19081	138	4	of	of	ADP
bracis-19081	138	5	0.9	0.9	NUM
bracis-19081	138	6	was	be	AUX
bracis-19081	138	7	selected	select	VERB
bracis-19081	138	8	and	and	CCONJ
bracis-19081	138	9	gradient	gradient	NOUN
bracis-19081	138	10	was	be	AUX
bracis-19081	138	11	clipped	clip	VERB
bracis-19081	138	12	at	at	ADP
bracis-19081	138	13	5.0	5.0	NUM
bracis-19081	138	14	.	.	PUNCT
bracis-19081	139	1	learning	learn	VERB
bracis-19081	139	2	rates	rate	NOUN
bracis-19081	139	3	were	be	AUX
bracis-19081	139	4	0.015	0.015	NUM
bracis-19081	139	5	for	for	ADP
bracis-19081	139	6	both	both	DET
bracis-19081	139	7	models	model	NOUN
bracis-19081	139	8	trained	train	VERB
bracis-19081	139	9	on	on	ADP
bracis-19081	139	10	english	english	ADJ
bracis-19081	139	11	datasets	dataset	NOUN
bracis-19081	139	12	.	.	PUNCT
bracis-19081	140	1	for	for	ADP
bracis-19081	140	2	the	the	DET
bracis-19081	140	3	portuguese	portuguese	ADJ
bracis-19081	140	4	dataset	dataset	NOUN
bracis-19081	140	5	,	,	PUNCT
bracis-19081	140	6	learning	learn	VERB
bracis-19081	140	7	rates	rate	NOUN
bracis-19081	140	8	of	of	ADP
bracis-19081	140	9	0.010	0.010	NUM
bracis-19081	140	10	and	and	CCONJ
bracis-19081	140	11	0.0025	0.0025	NUM
bracis-19081	140	12	were	be	AUX
bracis-19081	140	13	selected	select	VERB
bracis-19081	140	14	for	for	ADP
bracis-19081	140	15	the	the	DET
bracis-19081	140	16	cnn	cnn	PROPN
bracis-19081	140	17	-	-	PUNCT
bracis-19081	140	18	cnn	cnn	PROPN
bracis-19081	140	19	-	-	PUNCT
bracis-19081	140	20	lstm	lstm	PROPN
bracis-19081	140	21	and	and	CCONJ
bracis-19081	140	22	cnn	cnn	PROPN
bracis-19081	140	23	-	-	PUNCT
bracis-19081	140	24	bilstm	bilstm	NOUN
bracis-19081	140	25	-	-	PUNCT
bracis-19081	140	26	crf	crf	NOUN
bracis-19081	140	27	models	model	NOUN
bracis-19081	140	28	,	,	PUNCT
bracis-19081	140	29	respectively	respectively	ADV
bracis-19081	140	30	.	.	PUNCT
bracis-19081	141	1	baselines	baseline	NOUN
bracis-19081	141	2	and	and	CCONJ
bracis-19081	141	3	evaluation	evaluation	NOUN
bracis-19081	141	4	metrics	metric	NOUN
bracis-19081	141	5	for	for	ADP
bracis-19081	141	6	the	the	DET
bracis-19081	141	7	first	first	ADJ
bracis-19081	141	8	experiment	experiment	NOUN
bracis-19081	141	9	,	,	PUNCT
bracis-19081	141	10	the	the	DET
bracis-19081	141	11	baseline	baseline	NOUN
bracis-19081	141	12	to	to	PART
bracis-19081	141	13	compare	compare	VERB
bracis-19081	141	14	the	the	DET
bracis-19081	141	15	performance	performance	NOUN
bracis-19081	141	16	of	of	ADP
bracis-19081	141	17	the	the	DET
bracis-19081	141	18	proposed	propose	VERB
bracis-19081	141	19	asl	asl	PROPN
bracis-19081	141	20	algorithm	algorithm	NOUN
bracis-19081	141	21	with	with	ADP
bracis-19081	141	22	the	the	DET
bracis-19081	141	23	dute	dute	NOUN
bracis-19081	141	24	strategy	strategy	NOUN
bracis-19081	141	25	is	be	AUX
bracis-19081	141	26	the	the	DET
bracis-19081	141	27	deep	deep	ADJ
bracis-19081	141	28	active	active	ADJ
bracis-19081	141	29	learning	learning	NOUN
bracis-19081	141	30	algorithm	algorithm	NOUN
bracis-19081	141	31	proposed	propose	VERB
bracis-19081	141	32	by	by	ADP
bracis-19081	141	33	shen	shen	PROPN
bracis-19081	141	34	et	et	PROPN
bracis-19081	141	35	al	al	PROPN
bracis-19081	141	36	.	.	PUNCT
bracis-19081	142	1	[	[	X
bracis-19081	142	2	15	15	NUM
bracis-19081	142	3	]	]	PUNCT
bracis-19081	142	4	,	,	PUNCT
bracis-19081	142	5	using	use	VERB
bracis-19081	142	6	the	the	DET
bracis-19081	142	7	mnlp	mnlp	ADJ
bracis-19081	142	8	sampling	sample	VERB
bracis-19081	142	9	function	function	NOUN
bracis-19081	142	10	.	.	PUNCT
bracis-19081	143	1	one	one	NUM
bracis-19081	143	2	key	key	ADJ
bracis-19081	143	3	change	change	NOUN
bracis-19081	143	4	is	be	AUX
bracis-19081	143	5	that	that	SCONJ
bracis-19081	143	6	we	we	PRON
bracis-19081	143	7	do	do	AUX
bracis-19081	143	8	not	not	PART
bracis-19081	143	9	employ	employ	VERB
bracis-19081	143	10	early	early	ADJ
bracis-19081	143	11	stopping	stopping	NOUN
bracis-19081	143	12	based	base	VERB
bracis-19081	143	13	on	on	ADP
bracis-19081	143	14	a	a	DET
bracis-19081	143	15	validation	validation	NOUN
bracis-19081	143	16	set	set	VERB
bracis-19081	143	17	as	as	ADP
bracis-19081	143	18	the	the	DET
bracis-19081	143	19	original	original	ADJ
bracis-19081	143	20	work	work	NOUN
bracis-19081	143	21	,	,	PUNCT
bracis-19081	143	22	instead	instead	ADV
bracis-19081	143	23	we	we	PRON
bracis-19081	143	24	train	train	VERB
bracis-19081	143	25	the	the	DET
bracis-19081	143	26	machine	machine	NOUN
bracis-19081	143	27	learning	learn	VERB
bracis-19081	143	28	model	model	NOUN
bracis-19081	143	29	for	for	ADP
bracis-19081	143	30	the	the	DET
bracis-19081	143	31	full	full	ADJ
bracis-19081	143	32	number	number	NOUN
bracis-19081	143	33	of	of	ADP
bracis-19081	143	34	training	training	NOUN
bracis-19081	143	35	epochs	epoch	NOUN
bracis-19081	143	36	at	at	ADP
bracis-19081	143	37	each	each	DET
bracis-19081	143	38	iteration	iteration	NOUN
bracis-19081	143	39	of	of	ADP
bracis-19081	143	40	the	the	DET
bracis-19081	143	41	dal	dal	NOUN
bracis-19081	143	42	process	process	NOUN
bracis-19081	143	43	.	.	PUNCT
bracis-19081	144	1	this	this	DET
bracis-19081	144	2	change	change	NOUN
bracis-19081	144	3	is	be	AUX
bracis-19081	144	4	justified	justify	VERB
bracis-19081	144	5	by	by	ADP
bracis-19081	144	6	the	the	DET
bracis-19081	144	7	fact	fact	NOUN
bracis-19081	144	8	that	that	SCONJ
bracis-19081	144	9	the	the	DET
bracis-19081	144	10	early	early	ADJ
bracis-19081	144	11	stopping	stopping	NOUN
bracis-19081	144	12	is	be	AUX
bracis-19081	144	13	applied	apply	VERB
bracis-19081	144	14	mainly	mainly	ADV
bracis-19081	144	15	to	to	PART
bracis-19081	144	16	avoid	avoid	VERB
bracis-19081	144	17	overfitting	overfitting	NOUN
bracis-19081	144	18	of	of	ADP
bracis-19081	144	19	the	the	DET
bracis-19081	144	20	models	model	NOUN
bracis-19081	144	21	during	during	ADP
bracis-19081	144	22	training	training	NOUN
bracis-19081	144	23	,	,	PUNCT
bracis-19081	144	24	and	and	CCONJ
bracis-19081	144	25	throughout	throughout	ADP
bracis-19081	144	26	all	all	DET
bracis-19081	144	27	the	the	DET
bracis-19081	144	28	experiments	experiment	NOUN
bracis-19081	144	29	performed	perform	VERB
bracis-19081	144	30	this	this	DET
bracis-19081	144	31	phenomenon	phenomenon	NOUN
bracis-19081	144	32	did	do	AUX
bracis-19081	144	33	n’t	not	PART
bracis-19081	144	34	occur	occur	VERB
bracis-19081	144	35	.	.	PUNCT
bracis-19081	145	1	the	the	DET
bracis-19081	145	2	f1	f1	NOUN
bracis-19081	145	3	-	-	PUNCT
bracis-19081	145	4	scores	score	NOUN
bracis-19081	145	5	will	will	AUX
bracis-19081	145	6	be	be	AUX
bracis-19081	145	7	computed	compute	VERB
bracis-19081	145	8	on	on	ADP
bracis-19081	145	9	the	the	DET
bracis-19081	145	10	test	test	NOUN
bracis-19081	145	11	set	set	VERB
bracis-19081	145	12	at	at	ADP
bracis-19081	145	13	the	the	DET
bracis-19081	145	14	end	end	NOUN
bracis-19081	145	15	of	of	ADP
bracis-19081	145	16	the	the	DET
bracis-19081	145	17	training	training	NOUN
bracis-19081	145	18	process	process	NOUN
bracis-19081	145	19	.	.	PUNCT
bracis-19081	146	1	query	query	NOUN
bracis-19081	146	2	budget	budget	NOUN
bracis-19081	146	3	,	,	PUNCT
bracis-19081	146	4	number	number	NOUN
bracis-19081	146	5	of	of	ADP
bracis-19081	146	6	training	training	NOUN
bracis-19081	146	7	epochs	epoch	NOUN
bracis-19081	146	8	,	,	PUNCT
bracis-19081	146	9	and	and	CCONJ
bracis-19081	146	10	initial	initial	ADJ
bracis-19081	146	11	labeled	label	VERB
bracis-19081	146	12	set	set	VERB
bracis-19081	146	13	size	size	NOUN
bracis-19081	146	14	will	will	AUX
bracis-19081	146	15	be	be	AUX
bracis-19081	146	16	the	the	DET
bracis-19081	146	17	same	same	ADJ
bracis-19081	146	18	as	as	ADP
bracis-19081	146	19	those	those	PRON
bracis-19081	146	20	used	use	VERB
bracis-19081	146	21	by	by	ADP
bracis-19081	146	22	the	the	DET
bracis-19081	146	23	asl	asl	PROPN
bracis-19081	146	24	algorithm	algorithm	NOUN
bracis-19081	146	25	.	.	PUNCT
bracis-19081	147	1	for	for	ADP
bracis-19081	147	2	the	the	DET
bracis-19081	147	3	second	second	ADJ
bracis-19081	147	4	experiment	experiment	NOUN
bracis-19081	147	5	,	,	PUNCT
bracis-19081	147	6	the	the	DET
bracis-19081	147	7	ablation	ablation	NOUN
bracis-19081	147	8	study	study	NOUN
bracis-19081	147	9	,	,	PUNCT
bracis-19081	147	10	we	we	PRON
bracis-19081	147	11	wish	wish	VERB
bracis-19081	147	12	to	to	PART
bracis-19081	147	13	investigate	investigate	VERB
bracis-19081	147	14	the	the	DET
bracis-19081	147	15	impact	impact	NOUN
bracis-19081	147	16	of	of	ADP
bracis-19081	147	17	the	the	DET
bracis-19081	147	18	proposed	propose	VERB
bracis-19081	147	19	dute	dute	NOUN
bracis-19081	147	20	strategy	strategy	NOUN
bracis-19081	147	21	.	.	PUNCT
bracis-19081	148	1	as	as	ADP
bracis-19081	148	2	such	such	ADJ
bracis-19081	148	3	,	,	PUNCT
bracis-19081	148	4	the	the	DET
bracis-19081	148	5	baseline	baseline	NOUN
bracis-19081	148	6	will	will	AUX
bracis-19081	148	7	be	be	AUX
bracis-19081	148	8	the	the	DET
bracis-19081	148	9	proposed	propose	VERB
bracis-19081	148	10	asl	asl	NOUN
bracis-19081	148	11	algorithm	algorithm	NOUN
bracis-19081	148	12	without	without	ADP
bracis-19081	148	13	the	the	DET
bracis-19081	148	14	dute	dute	NOUN
bracis-19081	148	15	strategy	strategy	NOUN
bracis-19081	148	16	.	.	PUNCT
bracis-19081	149	1	a	a	DET
bracis-19081	149	2	trained	train	VERB
bracis-19081	149	3	model	model	NOUN
bracis-19081	149	4	’s	’s	PART
bracis-19081	149	5	performance	performance	NOUN
bracis-19081	149	6	will	will	AUX
bracis-19081	149	7	be	be	AUX
bracis-19081	149	8	evaluated	evaluate	VERB
bracis-19081	149	9	using	use	VERB
bracis-19081	149	10	the	the	DET
bracis-19081	149	11	exact	exact	ADJ
bracis-19081	149	12	-	-	PUNCT
bracis-19081	149	13	match	match	NOUN
bracis-19081	149	14	(	(	PUNCT
bracis-19081	149	15	i.e.	i.e.	X
bracis-19081	149	16	span	span	NOUN
bracis-19081	149	17	-	-	PUNCT
bracis-19081	149	18	based	base	VERB
bracis-19081	149	19	)	)	PUNCT
bracis-19081	149	20	micro	micro	ADJ
bracis-19081	149	21	-	-	ADJ
bracis-19081	149	22	averaged	average	VERB
bracis-19081	149	23	f1	f1	NOUN
bracis-19081	149	24	-	-	PUNCT
bracis-19081	149	25	score	score	NOUN
bracis-19081	149	26	on	on	ADP
bracis-19081	149	27	the	the	DET
bracis-19081	149	28	test	test	NOUN
bracis-19081	149	29	set	set	VERB
bracis-19081	149	30	.	.	PUNCT
bracis-19081	150	1	experiment	experiment	NOUN
bracis-19081	150	2	setup	setup	NOUN
bracis-19081	150	3	all	all	DET
bracis-19081	150	4	experiments	experiment	NOUN
bracis-19081	150	5	reported	report	VERB
bracis-19081	150	6	were	be	AUX
bracis-19081	150	7	implemented	implement	VERB
bracis-19081	150	8	and	and	CCONJ
bracis-19081	150	9	executed	execute	VERB
bracis-19081	150	10	on	on	ADP
bracis-19081	150	11	the	the	DET
bracis-19081	150	12	google	google	PROPN
bracis-19081	150	13	colab	colab	PROPN
bracis-19081	150	14	platform	platform	NOUN
bracis-19081	150	15	with	with	ADP
bracis-19081	150	16	a	a	DET
bracis-19081	150	17	pro	pro	ADJ
bracis-19081	150	18	subscription	subscription	NOUN
bracis-19081	150	19	using	use	VERB
bracis-19081	150	20	the	the	DET
bracis-19081	150	21	pytorch	pytorch	NOUN
bracis-19081	151	1	[	[	X
bracis-19081	151	2	9	9	NUM
bracis-19081	151	3	]	]	PUNCT
bracis-19081	151	4	framework	framework	NOUN
bracis-19081	151	5	.	.	PUNCT
bracis-19081	152	1	gpus	gpus	PROPN
bracis-19081	152	2	available	available	ADJ
bracis-19081	152	3	were	be	AUX
bracis-19081	152	4	the	the	DET
bracis-19081	152	5	tesla	tesla	PROPN
bracis-19081	152	6	p100	p100	PROPN
bracis-19081	152	7	,	,	PUNCT
bracis-19081	152	8	the	the	DET
bracis-19081	152	9	tesla	tesla	PROPN
bracis-19081	152	10	v100	v100	PROPN
bracis-19081	152	11	,	,	PUNCT
bracis-19081	152	12	and	and	CCONJ
bracis-19081	152	13	the	the	DET
bracis-19081	152	14	tesla	tesla	PROPN
bracis-19081	152	15	t4	t4	PROPN
bracis-19081	152	16	all	all	ADV
bracis-19081	152	17	with	with	ADP
bracis-19081	152	18	16	16	NUM
bracis-19081	152	19	gb	gb	NOUN
bracis-19081	152	20	.	.	PUNCT
bracis-19081	153	1	fig	fig	NOUN
bracis-19081	153	2	.	.	PUNCT
bracis-19081	154	1	2	2	X
bracis-19081	154	2	.	.	X
bracis-19081	154	3	comparison	comparison	NOUN
bracis-19081	154	4	between	between	ADP
bracis-19081	154	5	the	the	DET
bracis-19081	154	6	proposed	propose	VERB
bracis-19081	154	7	asl	asl	NOUN
bracis-19081	154	8	algorithm	algorithm	NOUN
bracis-19081	154	9	with	with	ADP
bracis-19081	154	10	the	the	DET
bracis-19081	154	11	dute	dute	NOUN
bracis-19081	154	12	strategy	strategy	NOUN
bracis-19081	154	13	(	(	PUNCT
bracis-19081	154	14	asl_dute	asl_dute	NOUN
bracis-19081	154	15	)	)	PUNCT
bracis-19081	154	16	and	and	CCONJ
bracis-19081	154	17	the	the	DET
bracis-19081	154	18	deep	deep	ADJ
bracis-19081	154	19	active	active	ADJ
bracis-19081	154	20	learning	learn	VERB
bracis-19081	154	21	algorithm	algorithm	NOUN
bracis-19081	154	22	(	(	PUNCT
bracis-19081	154	23	al	al	PROPN
bracis-19081	154	24	)	)	PUNCT
bracis-19081	154	25	.	.	PUNCT
bracis-19081	155	1	experiments	experiment	NOUN
bracis-19081	155	2	were	be	AUX
bracis-19081	155	3	performed	perform	VERB
bracis-19081	155	4	across	across	ADP
bracis-19081	155	5	all	all	DET
bracis-19081	155	6	datasets	dataset	NOUN
bracis-19081	155	7	with	with	ADP
bracis-19081	155	8	both	both	DET
bracis-19081	155	9	neural	neural	ADJ
bracis-19081	155	10	models	model	NOUN
bracis-19081	155	11	.	.	PUNCT
bracis-19081	156	1	the	the	DET
bracis-19081	156	2	x	x	PROPN
bracis-19081	156	3	axis	axis	NOUN
bracis-19081	156	4	represents	represent	VERB
bracis-19081	156	5	the	the	DET
bracis-19081	156	6	percentage	percentage	NOUN
bracis-19081	156	7	of	of	ADP
bracis-19081	156	8	the	the	DET
bracis-19081	156	9	whole	whole	ADJ
bracis-19081	156	10	training	training	NOUN
bracis-19081	156	11	set	set	NOUN
bracis-19081	156	12	that	that	PRON
bracis-19081	156	13	has	have	AUX
bracis-19081	156	14	been	be	AUX
bracis-19081	156	15	annotated	annotate	VERB
bracis-19081	156	16	by	by	ADP
bracis-19081	156	17	the	the	DET
bracis-19081	156	18	oracle	oracle	NOUN
bracis-19081	156	19	.	.	PUNCT
bracis-19081	157	1	full	full	ADJ
bracis-19081	157	2	size	size	NOUN
bracis-19081	157	3	image	image	NOUN
bracis-19081	157	4	3	3	NUM
bracis-19081	157	5	results	result	VERB
bracis-19081	157	6	the	the	DET
bracis-19081	157	7	results	result	NOUN
bracis-19081	157	8	for	for	ADP
bracis-19081	157	9	the	the	DET
bracis-19081	157	10	experiments	experiment	NOUN
bracis-19081	157	11	on	on	ADP
bracis-19081	157	12	the	the	DET
bracis-19081	157	13	proposed	propose	VERB
bracis-19081	157	14	deep	deep	ADJ
bracis-19081	157	15	active	active	ADJ
bracis-19081	157	16	-	-	PUNCT
bracis-19081	157	17	self	self	NOUN
bracis-19081	157	18	learning	learn	VERB
bracis-19081	157	19	algorithm	algorithm	NOUN
bracis-19081	157	20	along	along	ADP
bracis-19081	157	21	with	with	ADP
bracis-19081	157	22	its	its	PRON
bracis-19081	157	23	baselines	baseline	NOUN
bracis-19081	157	24	are	be	AUX
bracis-19081	157	25	presented	present	VERB
bracis-19081	157	26	in	in	ADP
bracis-19081	157	27	this	this	DET
bracis-19081	157	28	section	section	NOUN
bracis-19081	157	29	.	.	PUNCT
bracis-19081	158	1	we	we	PRON
bracis-19081	158	2	also	also	ADV
bracis-19081	158	3	show	show	VERB
bracis-19081	158	4	an	an	DET
bracis-19081	158	5	ablation	ablation	NOUN
bracis-19081	158	6	study	study	NOUN
bracis-19081	158	7	conducted	conduct	VERB
bracis-19081	158	8	to	to	PART
bracis-19081	158	9	investigate	investigate	VERB
bracis-19081	158	10	the	the	DET
bracis-19081	158	11	impact	impact	NOUN
bracis-19081	158	12	of	of	ADP
bracis-19081	158	13	the	the	DET
bracis-19081	158	14	dute	dute	NOUN
bracis-19081	158	15	strategy	strategy	NOUN
bracis-19081	158	16	on	on	ADP
bracis-19081	158	17	the	the	DET
bracis-19081	158	18	performance	performance	NOUN
bracis-19081	158	19	and	and	CCONJ
bracis-19081	158	20	execution	execution	NOUN
bracis-19081	158	21	time	time	NOUN
bracis-19081	158	22	of	of	ADP
bracis-19081	158	23	the	the	DET
bracis-19081	158	24	proposed	propose	VERB
bracis-19081	158	25	asl	asl	PROPN
bracis-19081	158	26	algorithm	algorithm	NOUN
bracis-19081	158	27	.	.	PUNCT
bracis-19081	159	1	3.1	3.1	NUM
bracis-19081	159	2	deep	deep	ADJ
bracis-19081	159	3	active	active	ADJ
bracis-19081	159	4	-	-	PUNCT
bracis-19081	159	5	self	self	NOUN
bracis-19081	159	6	learning	learning	NOUN
bracis-19081	159	7	with	with	ADP
bracis-19081	159	8	 	 	SPACE
bracis-19081	159	9	dute	dute	NOUN
bracis-19081	159	10	strategy	strategy	NOUN
bracis-19081	159	11	figure	figure	NOUN
bracis-19081	159	12	 	 	SPACE
bracis-19081	159	13	2	2	NUM
bracis-19081	159	14	shows	show	VERB
bracis-19081	159	15	the	the	DET
bracis-19081	159	16	performance	performance	NOUN
bracis-19081	159	17	curves	curve	NOUN
bracis-19081	159	18	comparing	compare	VERB
bracis-19081	159	19	the	the	DET
bracis-19081	159	20	traditional	traditional	ADJ
bracis-19081	159	21	deep	deep	ADJ
bracis-19081	159	22	active	active	ADJ
bracis-19081	159	23	learning	learn	VERB
bracis-19081	159	24	algorithms	algorithm	NOUN
bracis-19081	159	25	found	find	VERB
bracis-19081	159	26	in	in	ADP
bracis-19081	159	27	the	the	DET
bracis-19081	159	28	literature	literature	NOUN
bracis-19081	159	29	and	and	CCONJ
bracis-19081	159	30	the	the	DET
bracis-19081	159	31	proposed	propose	VERB
bracis-19081	159	32	deep	deep	ADJ
bracis-19081	159	33	active	active	ADJ
bracis-19081	159	34	-	-	PUNCT
bracis-19081	159	35	self	self	NOUN
bracis-19081	159	36	learning	learn	VERB
bracis-19081	159	37	algorithm	algorithm	NOUN
bracis-19081	159	38	with	with	ADP
bracis-19081	159	39	dute	dute	NOUN
bracis-19081	159	40	strategy	strategy	NOUN
bracis-19081	159	41	.	.	PUNCT
bracis-19081	160	1	each	each	DET
bracis-19081	160	2	experiment	experiment	NOUN
bracis-19081	160	3	was	be	AUX
bracis-19081	160	4	executed	execute	VERB
bracis-19081	160	5	six	six	NUM
bracis-19081	160	6	times	time	NOUN
bracis-19081	160	7	with	with	ADP
bracis-19081	160	8	unique	unique	ADJ
bracis-19081	160	9	initial	initial	ADJ
bracis-19081	160	10	labeled	label	VERB
bracis-19081	160	11	sets	set	NOUN
bracis-19081	160	12	,	,	PUNCT
bracis-19081	160	13	and	and	CCONJ
bracis-19081	160	14	we	we	PRON
bracis-19081	160	15	report	report	VERB
bracis-19081	160	16	the	the	DET
bracis-19081	160	17	mean	mean	ADJ
bracis-19081	160	18	performance	performance	NOUN
bracis-19081	160	19	curve	curve	NOUN
bracis-19081	160	20	for	for	ADP
bracis-19081	160	21	each	each	PRON
bracis-19081	160	22	of	of	ADP
bracis-19081	160	23	them	they	PRON
bracis-19081	160	24	.	.	PUNCT
bracis-19081	161	1	the	the	DET
bracis-19081	161	2	same	same	ADJ
bracis-19081	161	3	six	six	NUM
bracis-19081	161	4	initial	initial	ADJ
bracis-19081	161	5	labeled	label	VERB
bracis-19081	161	6	sets	set	NOUN
bracis-19081	161	7	were	be	AUX
bracis-19081	161	8	used	use	VERB
bracis-19081	161	9	for	for	ADP
bracis-19081	161	10	experiments	experiment	NOUN
bracis-19081	161	11	on	on	ADP
bracis-19081	161	12	the	the	DET
bracis-19081	161	13	same	same	ADJ
bracis-19081	161	14	dataset	dataset	NOUN
bracis-19081	161	15	for	for	ADP
bracis-19081	161	16	all	all	DET
bracis-19081	161	17	training	training	NOUN
bracis-19081	161	18	algorithms	algorithm	NOUN
bracis-19081	161	19	and	and	CCONJ
bracis-19081	161	20	neural	neural	ADJ
bracis-19081	161	21	models	model	NOUN
bracis-19081	161	22	.	.	PUNCT
bracis-19081	162	1	the	the	DET
bracis-19081	162	2	algorithms	algorithm	NOUN
bracis-19081	162	3	were	be	AUX
bracis-19081	162	4	executed	execute	VERB
bracis-19081	162	5	until	until	SCONJ
bracis-19081	162	6	at	at	ADP
bracis-19081	162	7	least	least	ADV
bracis-19081	162	8	50	50	NUM
bracis-19081	162	9	%	%	NOUN
bracis-19081	162	10	of	of	ADP
bracis-19081	162	11	the	the	DET
bracis-19081	162	12	training	training	NOUN
bracis-19081	162	13	set	set	NOUN
bracis-19081	162	14	had	have	AUX
bracis-19081	162	15	been	be	AUX
bracis-19081	162	16	annotated	annotate	VERB
bracis-19081	162	17	by	by	ADP
bracis-19081	162	18	the	the	DET
bracis-19081	162	19	oracle	oracle	NOUN
bracis-19081	162	20	,	,	PUNCT
bracis-19081	162	21	in	in	ADP
bracis-19081	162	22	a	a	DET
bracis-19081	162	23	similar	similar	ADJ
bracis-19081	162	24	setup	setup	NOUN
bracis-19081	162	25	used	use	VERB
bracis-19081	162	26	in	in	ADP
bracis-19081	162	27	previous	previous	ADJ
bracis-19081	162	28	works	work	NOUN
bracis-19081	162	29	[	[	X
bracis-19081	162	30	15	15	NUM
bracis-19081	162	31	,	,	PUNCT
bracis-19081	162	32	16	16	NUM
bracis-19081	162	33	]	]	PUNCT
bracis-19081	162	34	.	.	PUNCT
bracis-19081	163	1	it	it	PRON
bracis-19081	163	2	has	have	AUX
bracis-19081	163	3	been	be	AUX
bracis-19081	163	4	observed	observe	VERB
bracis-19081	163	5	that	that	SCONJ
bracis-19081	163	6	the	the	DET
bracis-19081	163	7	proposed	propose	VERB
bracis-19081	163	8	asl	asl	PROPN
bracis-19081	163	9	algorithm	algorithm	NOUN
bracis-19081	163	10	achieved	achieve	VERB
bracis-19081	163	11	similar	similar	ADJ
bracis-19081	163	12	performance	performance	NOUN
bracis-19081	163	13	to	to	ADP
bracis-19081	163	14	the	the	DET
bracis-19081	163	15	deep	deep	ADJ
bracis-19081	163	16	active	active	ADJ
bracis-19081	163	17	learning	learning	NOUN
bracis-19081	163	18	baseline	baseline	NOUN
bracis-19081	163	19	for	for	ADP
bracis-19081	163	20	most	most	ADJ
bracis-19081	163	21	experiments	experiment	NOUN
bracis-19081	163	22	.	.	PUNCT
bracis-19081	164	1	one	one	NUM
bracis-19081	164	2	advantage	advantage	NOUN
bracis-19081	164	3	of	of	ADP
bracis-19081	164	4	the	the	DET
bracis-19081	164	5	active	active	ADJ
bracis-19081	164	6	-	-	PUNCT
bracis-19081	164	7	self	self	NOUN
bracis-19081	164	8	learning	learn	VERB
bracis-19081	164	9	algorithm	algorithm	NOUN
bracis-19081	164	10	is	be	AUX
bracis-19081	164	11	its	its	PRON
bracis-19081	164	12	capabilities	capability	NOUN
bracis-19081	164	13	of	of	ADP
bracis-19081	164	14	allowing	allow	VERB
bracis-19081	164	15	for	for	ADP
bracis-19081	164	16	self	self	NOUN
bracis-19081	164	17	-	-	PUNCT
bracis-19081	164	18	labeling	labeling	NOUN
bracis-19081	164	19	,	,	PUNCT
bracis-19081	164	20	thus	thus	ADV
bracis-19081	164	21	potentially	potentially	ADV
bracis-19081	164	22	reducing	reduce	VERB
bracis-19081	164	23	human	human	ADJ
bracis-19081	164	24	annotation	annotation	NOUN
bracis-19081	164	25	efforts	effort	NOUN
bracis-19081	164	26	.	.	PUNCT
bracis-19081	165	1	figure	figure	VERB
bracis-19081	165	2	 	 	SPACE
bracis-19081	165	3	3	3	NUM
bracis-19081	165	4	reports	report	VERB
bracis-19081	165	5	the	the	DET
bracis-19081	165	6	performance	performance	NOUN
bracis-19081	165	7	of	of	ADP
bracis-19081	165	8	the	the	DET
bracis-19081	165	9	self	self	NOUN
bracis-19081	165	10	-	-	PUNCT
bracis-19081	165	11	labeling	labeling	NOUN
bracis-19081	165	12	process	process	NOUN
bracis-19081	165	13	throughout	throughout	ADP
bracis-19081	165	14	the	the	DET
bracis-19081	165	15	active	active	ADJ
bracis-19081	165	16	-	-	PUNCT
bracis-19081	165	17	self	self	NOUN
bracis-19081	165	18	learning	learn	VERB
bracis-19081	165	19	algorithm	algorithm	NOUN
bracis-19081	165	20	.	.	PUNCT
bracis-19081	166	1	the	the	DET
bracis-19081	166	2	figures	figure	NOUN
bracis-19081	166	3	present	present	VERB
bracis-19081	166	4	the	the	DET
bracis-19081	166	5	percentage	percentage	NOUN
bracis-19081	166	6	of	of	ADP
bracis-19081	166	7	self	self	NOUN
bracis-19081	166	8	-	-	PUNCT
bracis-19081	166	9	labeled	label	VERB
bracis-19081	166	10	samples	sample	NOUN
bracis-19081	166	11	by	by	ADP
bracis-19081	166	12	the	the	DET
bracis-19081	166	13	percentage	percentage	NOUN
bracis-19081	166	14	of	of	ADP
bracis-19081	166	15	actively	actively	ADV
bracis-19081	166	16	labeled	label	VERB
bracis-19081	166	17	samples	sample	NOUN
bracis-19081	166	18	(	(	PUNCT
bracis-19081	166	19	i.e.	i.e.	X
bracis-19081	166	20	human	human	ADJ
bracis-19081	166	21	annotation	annotation	NOUN
bracis-19081	166	22	)	)	PUNCT
bracis-19081	166	23	and	and	CCONJ
bracis-19081	166	24	discriminates	discriminate	VERB
bracis-19081	166	25	the	the	DET
bracis-19081	166	26	amount	amount	NOUN
bracis-19081	166	27	of	of	ADP
bracis-19081	166	28	correctly	correctly	ADV
bracis-19081	166	29	and	and	CCONJ
bracis-19081	166	30	wrongly	wrongly	ADV
bracis-19081	166	31	self	self	NOUN
bracis-19081	166	32	-	-	PUNCT
bracis-19081	166	33	labeled	label	VERB
bracis-19081	166	34	tokens	token	NOUN
bracis-19081	166	35	.	.	PUNCT
bracis-19081	167	1	in	in	ADP
bracis-19081	167	2	general	general	ADJ
bracis-19081	167	3	,	,	PUNCT
bracis-19081	167	4	the	the	DET
bracis-19081	167	5	trained	train	VERB
bracis-19081	167	6	model	model	NOUN
bracis-19081	167	7	predicted	predict	VERB
bracis-19081	167	8	most	most	ADJ
bracis-19081	167	9	tokens	token	NOUN
bracis-19081	167	10	correctly	correctly	ADV
bracis-19081	167	11	at	at	ADP
bracis-19081	167	12	all	all	DET
bracis-19081	167	13	iterations	iteration	NOUN
bracis-19081	167	14	of	of	ADP
bracis-19081	167	15	the	the	DET
bracis-19081	167	16	algorithm	algorithm	NOUN
bracis-19081	167	17	.	.	PUNCT
bracis-19081	168	1	across	across	ADP
bracis-19081	168	2	all	all	DET
bracis-19081	168	3	experiments	experiment	NOUN
bracis-19081	168	4	performed	perform	VERB
bracis-19081	168	5	,	,	PUNCT
bracis-19081	168	6	\(1.31\%\	\(1.31\%\	PROPN
bracis-19081	168	7	)	)	PUNCT
bracis-19081	168	8	was	be	AUX
bracis-19081	168	9	the	the	DET
bracis-19081	168	10	highest	high	ADJ
bracis-19081	168	11	percentage	percentage	NOUN
bracis-19081	168	12	of	of	ADP
bracis-19081	168	13	tokens	token	NOUN
bracis-19081	168	14	to	to	PART
bracis-19081	168	15	be	be	AUX
bracis-19081	168	16	mislabeled	mislabele	VERB
bracis-19081	168	17	by	by	ADP
bracis-19081	168	18	the	the	DET
bracis-19081	168	19	trained	train	VERB
bracis-19081	168	20	model	model	NOUN
bracis-19081	168	21	in	in	ADP
bracis-19081	168	22	any	any	DET
bracis-19081	168	23	given	give	VERB
bracis-19081	168	24	iteration	iteration	NOUN
bracis-19081	168	25	of	of	ADP
bracis-19081	168	26	the	the	DET
bracis-19081	168	27	asl	asl	NOUN
bracis-19081	168	28	process	process	NOUN
bracis-19081	168	29	.	.	PUNCT
bracis-19081	169	1	even	even	ADV
bracis-19081	169	2	though	though	SCONJ
bracis-19081	169	3	most	most	ADJ
bracis-19081	169	4	tokens	token	NOUN
bracis-19081	169	5	were	be	AUX
bracis-19081	169	6	correctly	correctly	ADV
bracis-19081	169	7	self	self	NOUN
bracis-19081	169	8	-	-	PUNCT
bracis-19081	169	9	labeled	label	VERB
bracis-19081	169	10	,	,	PUNCT
bracis-19081	169	11	little	little	ADJ
bracis-19081	169	12	impact	impact	NOUN
bracis-19081	169	13	has	have	AUX
bracis-19081	169	14	been	be	AUX
bracis-19081	169	15	observed	observe	VERB
bracis-19081	169	16	on	on	ADP
bracis-19081	169	17	the	the	DET
bracis-19081	169	18	trained	train	VERB
bracis-19081	169	19	model	model	NOUN
bracis-19081	169	20	’s	’s	PART
bracis-19081	169	21	performance	performance	NOUN
bracis-19081	169	22	due	due	ADP
bracis-19081	169	23	to	to	ADP
bracis-19081	169	24	self	self	NOUN
bracis-19081	169	25	-	-	PUNCT
bracis-19081	169	26	training	training	NOUN
bracis-19081	169	27	.	.	PUNCT
bracis-19081	170	1	this	this	PRON
bracis-19081	170	2	may	may	AUX
bracis-19081	170	3	be	be	AUX
bracis-19081	170	4	justified	justify	VERB
bracis-19081	170	5	by	by	ADP
bracis-19081	170	6	the	the	DET
bracis-19081	170	7	fact	fact	NOUN
bracis-19081	170	8	that	that	SCONJ
bracis-19081	170	9	ner	ner	NOUN
bracis-19081	170	10	datasets	dataset	NOUN
bracis-19081	170	11	are	be	AUX
bracis-19081	170	12	imbalanced	imbalance	VERB
bracis-19081	170	13	,	,	PUNCT
bracis-19081	170	14	with	with	ADP
bracis-19081	170	15	most	most	ADJ
bracis-19081	170	16	tokens	token	NOUN
bracis-19081	170	17	not	not	PART
bracis-19081	170	18	being	be	AUX
bracis-19081	170	19	a	a	DET
bracis-19081	170	20	part	part	NOUN
bracis-19081	170	21	of	of	ADP
bracis-19081	170	22	a	a	DET
bracis-19081	170	23	named	name	VERB
bracis-19081	170	24	entity	entity	NOUN
bracis-19081	170	25	,	,	PUNCT
bracis-19081	170	26	and	and	CCONJ
bracis-19081	170	27	entity	entity	NOUN
bracis-19081	170	28	level	level	NOUN
bracis-19081	170	29	annotations	annotation	NOUN
bracis-19081	170	30	being	be	AUX
bracis-19081	170	31	unreliable	unreliable	ADJ
bracis-19081	170	32	at	at	ADP
bracis-19081	170	33	earlier	early	ADJ
bracis-19081	170	34	rounds	round	NOUN
bracis-19081	170	35	.	.	PUNCT
bracis-19081	171	1	fig	fig	NOUN
bracis-19081	171	2	.	.	PUNCT
bracis-19081	172	1	3	3	X
bracis-19081	172	2	.	.	X
bracis-19081	172	3	comparison	comparison	NOUN
bracis-19081	172	4	between	between	ADP
bracis-19081	172	5	the	the	DET
bracis-19081	172	6	correctly	correctly	ADV
bracis-19081	172	7	and	and	CCONJ
bracis-19081	172	8	wrongly	wrongly	ADV
bracis-19081	172	9	self	self	NOUN
bracis-19081	172	10	-	-	PUNCT
bracis-19081	172	11	annotated	annotate	VERB
bracis-19081	172	12	samples	sample	NOUN
bracis-19081	172	13	,	,	PUNCT
bracis-19081	172	14	at	at	ADP
bracis-19081	172	15	token	token	ADJ
bracis-19081	172	16	level	level	NOUN
bracis-19081	172	17	,	,	PUNCT
bracis-19081	172	18	for	for	SCONJ
bracis-19081	172	19	the	the	DET
bracis-19081	172	20	experiments	experiment	NOUN
bracis-19081	172	21	performed	perform	VERB
bracis-19081	172	22	on	on	ADP
bracis-19081	172	23	all	all	DET
bracis-19081	172	24	three	three	NUM
bracis-19081	172	25	datasets	dataset	NOUN
bracis-19081	172	26	.	.	PUNCT
bracis-19081	173	1	note	note	VERB
bracis-19081	173	2	that	that	SCONJ
bracis-19081	173	3	the	the	DET
bracis-19081	173	4	y	y	NOUN
bracis-19081	173	5	-	-	PUNCT
bracis-19081	173	6	axis	axis	NOUN
bracis-19081	173	7	on	on	ADP
bracis-19081	173	8	each	each	DET
bracis-19081	173	9	graph	graph	NOUN
bracis-19081	173	10	presents	present	VERB
bracis-19081	173	11	the	the	DET
bracis-19081	173	12	percentage	percentage	NOUN
bracis-19081	173	13	of	of	ADP
bracis-19081	173	14	the	the	DET
bracis-19081	173	15	whole	whole	ADJ
bracis-19081	173	16	training	training	NOUN
bracis-19081	173	17	set	set	NOUN
bracis-19081	173	18	that	that	PRON
bracis-19081	173	19	has	have	AUX
bracis-19081	173	20	been	be	AUX
bracis-19081	173	21	self	self	NOUN
bracis-19081	173	22	-	-	PUNCT
bracis-19081	173	23	labeled	label	VERB
bracis-19081	173	24	by	by	ADP
bracis-19081	173	25	the	the	DET
bracis-19081	173	26	trained	train	VERB
bracis-19081	173	27	model	model	NOUN
bracis-19081	173	28	in	in	ADP
bracis-19081	173	29	a	a	DET
bracis-19081	173	30	given	give	VERB
bracis-19081	173	31	iteration	iteration	NOUN
bracis-19081	173	32	of	of	ADP
bracis-19081	173	33	the	the	DET
bracis-19081	173	34	asl	asl	NOUN
bracis-19081	173	35	algorithm	algorithm	NOUN
bracis-19081	173	36	,	,	PUNCT
bracis-19081	173	37	while	while	SCONJ
bracis-19081	173	38	the	the	DET
bracis-19081	173	39	x	x	ADJ
bracis-19081	173	40	-	-	ADJ
bracis-19081	173	41	axis	axis	NOUN
bracis-19081	173	42	presents	present	VERB
bracis-19081	173	43	the	the	DET
bracis-19081	173	44	percentage	percentage	NOUN
bracis-19081	173	45	of	of	ADP
bracis-19081	173	46	the	the	DET
bracis-19081	173	47	whole	whole	ADJ
bracis-19081	173	48	training	training	NOUN
bracis-19081	173	49	set	set	NOUN
bracis-19081	173	50	that	that	PRON
bracis-19081	173	51	has	have	AUX
bracis-19081	173	52	been	be	AUX
bracis-19081	173	53	labeled	label	VERB
bracis-19081	173	54	by	by	ADP
bracis-19081	173	55	the	the	DET
bracis-19081	173	56	human	human	ADJ
bracis-19081	173	57	annotator	annotator	NOUN
bracis-19081	173	58	.	.	PUNCT
bracis-19081	174	1	full	full	ADJ
bracis-19081	174	2	size	size	NOUN
bracis-19081	174	3	image	image	NOUN
bracis-19081	174	4	3.2	3.2	NUM
bracis-19081	174	5	ablation	ablation	NOUN
bracis-19081	174	6	study	study	NOUN
bracis-19081	174	7	next	next	ADV
bracis-19081	174	8	we	we	PRON
bracis-19081	174	9	conduct	conduct	VERB
bracis-19081	174	10	an	an	DET
bracis-19081	174	11	ablation	ablation	NOUN
bracis-19081	174	12	study	study	NOUN
bracis-19081	174	13	to	to	PART
bracis-19081	174	14	investigate	investigate	VERB
bracis-19081	174	15	the	the	DET
bracis-19081	174	16	impact	impact	NOUN
bracis-19081	174	17	of	of	ADP
bracis-19081	174	18	the	the	DET
bracis-19081	174	19	proposed	propose	VERB
bracis-19081	174	20	dute	dute	NOUN
bracis-19081	174	21	strategy	strategy	NOUN
bracis-19081	174	22	on	on	ADP
bracis-19081	174	23	the	the	DET
bracis-19081	174	24	performance	performance	NOUN
bracis-19081	174	25	and	and	CCONJ
bracis-19081	174	26	execution	execution	NOUN
bracis-19081	174	27	time	time	NOUN
bracis-19081	174	28	of	of	ADP
bracis-19081	174	29	the	the	DET
bracis-19081	174	30	proposed	propose	VERB
bracis-19081	174	31	deep	deep	ADJ
bracis-19081	174	32	active	active	ADJ
bracis-19081	174	33	-	-	PUNCT
bracis-19081	174	34	self	self	NOUN
bracis-19081	174	35	learning	learn	VERB
bracis-19081	174	36	algorithm	algorithm	NOUN
bracis-19081	174	37	.	.	PUNCT
bracis-19081	175	1	differently	differently	ADV
bracis-19081	175	2	from	from	ADP
bracis-19081	175	3	the	the	DET
bracis-19081	175	4	previous	previous	ADJ
bracis-19081	175	5	experiment	experiment	NOUN
bracis-19081	175	6	,	,	PUNCT
bracis-19081	175	7	in	in	ADP
bracis-19081	175	8	this	this	DET
bracis-19081	175	9	ablation	ablation	NOUN
bracis-19081	175	10	study	study	NOUN
bracis-19081	175	11	we	we	PRON
bracis-19081	175	12	executed	execute	VERB
bracis-19081	175	13	the	the	DET
bracis-19081	175	14	algorithms	algorithm	NOUN
bracis-19081	175	15	until	until	SCONJ
bracis-19081	175	16	at	at	ADV
bracis-19081	175	17	least	least	ADV
bracis-19081	175	18	30	30	NUM
bracis-19081	175	19	%	%	NOUN
bracis-19081	175	20	of	of	ADP
bracis-19081	175	21	the	the	DET
bracis-19081	175	22	training	training	NOUN
bracis-19081	175	23	set	set	NOUN
bracis-19081	175	24	had	have	AUX
bracis-19081	175	25	been	be	AUX
bracis-19081	175	26	annotated	annotate	VERB
bracis-19081	175	27	by	by	ADP
bracis-19081	175	28	the	the	DET
bracis-19081	175	29	oracle	oracle	PROPN
bracis-19081	175	30	.	.	PUNCT
bracis-19081	176	1	figure	figure	NOUN
bracis-19081	176	2	 	 	SPACE
bracis-19081	176	3	4	4	NUM
bracis-19081	176	4	compares	compare	VERB
bracis-19081	176	5	the	the	DET
bracis-19081	176	6	performance	performance	NOUN
bracis-19081	176	7	of	of	ADP
bracis-19081	176	8	the	the	DET
bracis-19081	176	9	asl	asl	NOUN
bracis-19081	176	10	algorithm	algorithm	NOUN
bracis-19081	176	11	with	with	ADP
bracis-19081	176	12	and	and	CCONJ
bracis-19081	176	13	without	without	ADP
bracis-19081	176	14	the	the	DET
bracis-19081	176	15	dute	dute	NOUN
bracis-19081	176	16	strategy	strategy	NOUN
bracis-19081	176	17	,	,	PUNCT
bracis-19081	176	18	while	while	SCONJ
bracis-19081	176	19	table	table	NOUN
bracis-19081	176	20	 	 	SPACE
bracis-19081	176	21	2	2	NUM
bracis-19081	176	22	reports	report	NOUN
bracis-19081	176	23	the	the	DET
bracis-19081	176	24	mean	mean	ADJ
bracis-19081	176	25	and	and	CCONJ
bracis-19081	176	26	standard	standard	ADJ
bracis-19081	176	27	deviation	deviation	NOUN
bracis-19081	176	28	for	for	ADP
bracis-19081	176	29	the	the	DET
bracis-19081	176	30	execution	execution	NOUN
bracis-19081	176	31	times	time	NOUN
bracis-19081	176	32	of	of	ADP
bracis-19081	176	33	the	the	DET
bracis-19081	176	34	simulations	simulation	NOUN
bracis-19081	176	35	.	.	PUNCT
bracis-19081	177	1	it	it	PRON
bracis-19081	177	2	has	have	AUX
bracis-19081	177	3	been	be	AUX
bracis-19081	177	4	observed	observe	VERB
bracis-19081	177	5	that	that	SCONJ
bracis-19081	177	6	for	for	ADP
bracis-19081	177	7	all	all	DET
bracis-19081	177	8	the	the	DET
bracis-19081	177	9	experiments	experiment	NOUN
bracis-19081	177	10	conducted	conduct	VERB
bracis-19081	177	11	,	,	PUNCT
bracis-19081	177	12	the	the	DET
bracis-19081	177	13	dute	dute	NOUN
bracis-19081	177	14	strategy	strategy	NOUN
bracis-19081	177	15	is	be	AUX
bracis-19081	177	16	capable	capable	ADJ
bracis-19081	177	17	of	of	ADP
bracis-19081	177	18	significantly	significantly	ADV
bracis-19081	177	19	reducing	reduce	VERB
bracis-19081	177	20	execution	execution	NOUN
bracis-19081	177	21	time	time	NOUN
bracis-19081	177	22	,	,	PUNCT
bracis-19081	177	23	while	while	SCONJ
bracis-19081	177	24	maintaining	maintain	VERB
bracis-19081	177	25	similar	similar	ADJ
bracis-19081	177	26	model	model	NOUN
bracis-19081	177	27	performance	performance	NOUN
bracis-19081	177	28	.	.	PUNCT
bracis-19081	178	1	fig	fig	NOUN
bracis-19081	178	2	.	.	PUNCT
bracis-19081	179	1	4	4	X
bracis-19081	179	2	.	.	X
bracis-19081	179	3	comparison	comparison	NOUN
bracis-19081	179	4	of	of	ADP
bracis-19081	179	5	the	the	DET
bracis-19081	179	6	performance	performance	NOUN
bracis-19081	179	7	of	of	ADP
bracis-19081	179	8	a	a	DET
bracis-19081	179	9	model	model	NOUN
bracis-19081	179	10	trained	train	VERB
bracis-19081	179	11	through	through	ADP
bracis-19081	179	12	the	the	DET
bracis-19081	179	13	proposed	propose	VERB
bracis-19081	179	14	deep	deep	ADJ
bracis-19081	179	15	active	active	ADJ
bracis-19081	179	16	-	-	PUNCT
bracis-19081	179	17	self	self	NOUN
bracis-19081	179	18	learning	learn	VERB
bracis-19081	179	19	algorithm	algorithm	NOUN
bracis-19081	179	20	with	with	ADP
bracis-19081	179	21	and	and	CCONJ
bracis-19081	179	22	without	without	ADP
bracis-19081	179	23	the	the	DET
bracis-19081	179	24	dute	dute	NOUN
bracis-19081	179	25	strategy	strategy	NOUN
bracis-19081	179	26	.	.	PUNCT
bracis-19081	180	1	the	the	DET
bracis-19081	180	2	x	x	PROPN
bracis-19081	180	3	axis	axis	NOUN
bracis-19081	180	4	represents	represent	VERB
bracis-19081	180	5	the	the	DET
bracis-19081	180	6	percentage	percentage	NOUN
bracis-19081	180	7	of	of	ADP
bracis-19081	180	8	the	the	DET
bracis-19081	180	9	whole	whole	ADJ
bracis-19081	180	10	training	training	NOUN
bracis-19081	180	11	set	set	NOUN
bracis-19081	180	12	that	that	PRON
bracis-19081	180	13	has	have	AUX
bracis-19081	180	14	been	be	AUX
bracis-19081	180	15	annotated	annotate	VERB
bracis-19081	180	16	by	by	ADP
bracis-19081	180	17	the	the	DET
bracis-19081	180	18	oracle	oracle	NOUN
bracis-19081	180	19	.	.	PUNCT
bracis-19081	181	1	full	full	ADJ
bracis-19081	181	2	size	size	NOUN
bracis-19081	181	3	image	image	NOUN
bracis-19081	181	4	table	table	NOUN
bracis-19081	181	5	2	2	NUM
bracis-19081	181	6	.	.	PUNCT
bracis-19081	181	7	mean	mean	VERB
bracis-19081	181	8	and	and	CCONJ
bracis-19081	181	9	standard	standard	ADJ
bracis-19081	181	10	deviation	deviation	NOUN
bracis-19081	181	11	for	for	ADP
bracis-19081	181	12	the	the	DET
bracis-19081	181	13	execution	execution	NOUN
bracis-19081	181	14	time	time	NOUN
bracis-19081	181	15	of	of	ADP
bracis-19081	181	16	the	the	DET
bracis-19081	181	17	proposed	propose	VERB
bracis-19081	181	18	active	active	ADJ
bracis-19081	181	19	-	-	PUNCT
bracis-19081	181	20	self	self	NOUN
bracis-19081	181	21	learning	learn	VERB
bracis-19081	181	22	algorithm	algorithm	NOUN
bracis-19081	181	23	with	with	ADP
bracis-19081	181	24	and	and	CCONJ
bracis-19081	181	25	without	without	ADP
bracis-19081	181	26	the	the	DET
bracis-19081	181	27	dute	dute	NOUN
bracis-19081	181	28	strategy	strategy	NOUN
bracis-19081	181	29	,	,	PUNCT
bracis-19081	181	30	reported	report	VERB
bracis-19081	181	31	in	in	ADP
bracis-19081	181	32	units	unit	NOUN
bracis-19081	181	33	of	of	ADP
bracis-19081	181	34	minutes	minute	NOUN
bracis-19081	181	35	.	.	PUNCT
bracis-19081	182	1	execution	execution	NOUN
bracis-19081	182	2	times	time	NOUN
bracis-19081	182	3	are	be	AUX
bracis-19081	182	4	measured	measure	VERB
bracis-19081	182	5	with	with	ADP
bracis-19081	182	6	algorithms	algorithm	NOUN
bracis-19081	182	7	being	be	AUX
bracis-19081	182	8	stopped	stop	VERB
bracis-19081	182	9	when	when	SCONJ
bracis-19081	182	10	the	the	DET
bracis-19081	182	11	set	set	NOUN
bracis-19081	182	12	of	of	ADP
bracis-19081	182	13	samples	sample	NOUN
bracis-19081	182	14	annotated	annotate	VERB
bracis-19081	182	15	by	by	ADP
bracis-19081	182	16	the	the	DET
bracis-19081	182	17	human	human	ADJ
bracis-19081	182	18	annotator	annotator	NOUN
bracis-19081	182	19	reaches	reach	VERB
bracis-19081	182	20	30	30	NUM
bracis-19081	182	21	%	%	NOUN
bracis-19081	182	22	of	of	ADP
bracis-19081	182	23	the	the	DET
bracis-19081	182	24	entire	entire	ADJ
bracis-19081	182	25	training	training	NOUN
bracis-19081	182	26	set	set	NOUN
bracis-19081	182	27	.	.	PUNCT
bracis-19081	183	1	asl_dute	asl_dute	VERB
bracis-19081	183	2	and	and	CCONJ
bracis-19081	183	3	asl	asl	NOUN
bracis-19081	183	4	refer	refer	VERB
bracis-19081	183	5	to	to	ADP
bracis-19081	183	6	the	the	DET
bracis-19081	183	7	proposed	propose	VERB
bracis-19081	183	8	active	active	ADJ
bracis-19081	183	9	-	-	PUNCT
bracis-19081	183	10	self	self	NOUN
bracis-19081	183	11	learning	learn	VERB
bracis-19081	183	12	algorithm	algorithm	NOUN
bracis-19081	183	13	with	with	ADP
bracis-19081	183	14	and	and	CCONJ
bracis-19081	183	15	without	without	ADP
bracis-19081	183	16	the	the	DET
bracis-19081	183	17	dute	dute	NOUN
bracis-19081	183	18	strategy	strategy	NOUN
bracis-19081	183	19	,	,	PUNCT
bracis-19081	183	20	respectively.full	respectively.full	NOUN
bracis-19081	183	21	size	size	NOUN
bracis-19081	183	22	table	table	NOUN
bracis-19081	183	23	4	4	NUM
bracis-19081	183	24	conclusion	conclusion	NOUN
bracis-19081	183	25	from	from	ADP
bracis-19081	183	26	the	the	DET
bracis-19081	183	27	experiments	experiment	NOUN
bracis-19081	183	28	conducted	conduct	VERB
bracis-19081	183	29	,	,	PUNCT
bracis-19081	183	30	we	we	PRON
bracis-19081	183	31	noticed	notice	VERB
bracis-19081	183	32	that	that	SCONJ
bracis-19081	183	33	the	the	DET
bracis-19081	183	34	proposed	propose	VERB
bracis-19081	183	35	deep	deep	ADJ
bracis-19081	183	36	active	active	ADJ
bracis-19081	183	37	-	-	PUNCT
bracis-19081	183	38	self	self	NOUN
bracis-19081	183	39	learning	learn	VERB
bracis-19081	183	40	algorithm	algorithm	NOUN
bracis-19081	183	41	is	be	AUX
bracis-19081	183	42	capable	capable	ADJ
bracis-19081	183	43	of	of	ADP
bracis-19081	183	44	self	self	NOUN
bracis-19081	183	45	-	-	PUNCT
bracis-19081	183	46	annotating	annotate	VERB
bracis-19081	183	47	unlabeled	unlabele	VERB
bracis-19081	183	48	samples	sample	NOUN
bracis-19081	183	49	reliably	reliably	ADV
bracis-19081	183	50	.	.	PUNCT
bracis-19081	184	1	the	the	DET
bracis-19081	184	2	self	self	NOUN
bracis-19081	184	3	-	-	PUNCT
bracis-19081	184	4	training	training	NOUN
bracis-19081	184	5	has	have	AUX
bracis-19081	184	6	n’t	not	PART
bracis-19081	184	7	,	,	PUNCT
bracis-19081	184	8	however	however	ADV
bracis-19081	184	9	,	,	PUNCT
bracis-19081	184	10	shown	show	VERB
bracis-19081	184	11	significant	significant	ADJ
bracis-19081	184	12	impact	impact	NOUN
bracis-19081	184	13	on	on	ADP
bracis-19081	184	14	the	the	DET
bracis-19081	184	15	model	model	NOUN
bracis-19081	184	16	’s	’s	PART
bracis-19081	184	17	performance	performance	NOUN
bracis-19081	184	18	.	.	PUNCT
bracis-19081	185	1	the	the	DET
bracis-19081	185	2	proposed	propose	VERB
bracis-19081	185	3	dute	dute	NOUN
bracis-19081	185	4	strategy	strategy	NOUN
bracis-19081	185	5	has	have	AUX
bracis-19081	185	6	also	also	ADV
bracis-19081	185	7	shown	show	VERB
bracis-19081	185	8	promising	promising	ADJ
bracis-19081	185	9	results	result	NOUN
bracis-19081	185	10	,	,	PUNCT
bracis-19081	185	11	being	be	AUX
bracis-19081	185	12	capable	capable	ADJ
bracis-19081	185	13	of	of	ADP
bracis-19081	185	14	significantly	significantly	ADV
bracis-19081	185	15	reducing	reduce	VERB
bracis-19081	185	16	the	the	DET
bracis-19081	185	17	execution	execution	NOUN
bracis-19081	185	18	times	time	NOUN
bracis-19081	185	19	for	for	ADP
bracis-19081	185	20	simulations	simulation	NOUN
bracis-19081	185	21	of	of	ADP
bracis-19081	185	22	the	the	DET
bracis-19081	185	23	proposed	propose	VERB
bracis-19081	185	24	algorithm	algorithm	NOUN
bracis-19081	185	25	with	with	ADP
bracis-19081	185	26	little	little	ADJ
bracis-19081	185	27	impact	impact	NOUN
bracis-19081	185	28	on	on	ADP
bracis-19081	185	29	the	the	DET
bracis-19081	185	30	model	model	NOUN
bracis-19081	185	31	’s	’s	PART
bracis-19081	185	32	performance	performance	NOUN
bracis-19081	185	33	,	,	PUNCT
bracis-19081	185	34	while	while	SCONJ
bracis-19081	185	35	not	not	PART
bracis-19081	185	36	relying	rely	VERB
bracis-19081	185	37	on	on	ADP
bracis-19081	185	38	a	a	DET
bracis-19081	185	39	validation	validation	NOUN
bracis-19081	185	40	set	set	NOUN
bracis-19081	185	41	.	.	PUNCT
bracis-19081	186	1	one	one	NUM
bracis-19081	186	2	of	of	ADP
bracis-19081	186	3	the	the	DET
bracis-19081	186	4	main	main	ADJ
bracis-19081	186	5	limitations	limitation	NOUN
bracis-19081	186	6	of	of	ADP
bracis-19081	186	7	the	the	DET
bracis-19081	186	8	proposed	propose	VERB
bracis-19081	186	9	asl	asl	NOUN
bracis-19081	186	10	algorithm	algorithm	NOUN
bracis-19081	186	11	still	still	ADV
bracis-19081	186	12	continues	continue	VERB
bracis-19081	186	13	to	to	PART
bracis-19081	186	14	be	be	AUX
bracis-19081	186	15	its	its	PRON
bracis-19081	186	16	reliance	reliance	NOUN
bracis-19081	186	17	on	on	ADP
bracis-19081	186	18	labeled	label	VERB
bracis-19081	186	19	data	datum	NOUN
bracis-19081	186	20	for	for	ADP
bracis-19081	186	21	hyperparameter	hyperparameter	NOUN
bracis-19081	186	22	tuning	tuning	NOUN
bracis-19081	186	23	.	.	PUNCT
bracis-19081	187	1	while	while	SCONJ
bracis-19081	187	2	our	our	PRON
bracis-19081	187	3	dute	dute	NOUN
bracis-19081	187	4	strategy	strategy	NOUN
bracis-19081	187	5	effectively	effectively	ADV
bracis-19081	187	6	avoids	avoid	VERB
bracis-19081	187	7	using	use	VERB
bracis-19081	187	8	validation	validation	NOUN
bracis-19081	187	9	sets	set	NOUN
bracis-19081	187	10	throughout	throughout	ADP
bracis-19081	187	11	the	the	DET
bracis-19081	187	12	asl	asl	NOUN
bracis-19081	187	13	process	process	NOUN
bracis-19081	187	14	,	,	PUNCT
bracis-19081	187	15	we	we	PRON
bracis-19081	187	16	still	still	ADV
bracis-19081	187	17	used	use	VERB
bracis-19081	187	18	training	training	NOUN
bracis-19081	187	19	and	and	CCONJ
bracis-19081	187	20	validation	validation	NOUN
bracis-19081	187	21	sets	set	NOUN
bracis-19081	187	22	for	for	ADP
bracis-19081	187	23	tuning	tuning	NOUN
bracis-19081	187	24	of	of	ADP
bracis-19081	187	25	the	the	DET
bracis-19081	187	26	hyperparameters	hyperparameter	NOUN
bracis-19081	187	27	for	for	ADP
bracis-19081	187	28	the	the	DET
bracis-19081	187	29	neural	neural	ADJ
bracis-19081	187	30	models	model	NOUN
bracis-19081	187	31	and	and	CCONJ
bracis-19081	187	32	others	other	NOUN
bracis-19081	187	33	such	such	ADJ
bracis-19081	187	34	as	as	ADP
bracis-19081	187	35	learning	learn	VERB
bracis-19081	187	36	rates	rate	NOUN
bracis-19081	187	37	and	and	CCONJ
bracis-19081	187	38	batch	batch	NOUN
bracis-19081	187	39	sizes	size	NOUN
bracis-19081	187	40	.	.	PUNCT
bracis-19081	188	1	this	this	PRON
bracis-19081	188	2	still	still	ADV
bracis-19081	188	3	poses	pose	VERB
bracis-19081	188	4	one	one	NUM
bracis-19081	188	5	of	of	ADP
bracis-19081	188	6	the	the	DET
bracis-19081	188	7	biggest	big	ADJ
bracis-19081	188	8	limitations	limitation	NOUN
bracis-19081	188	9	to	to	ADP
bracis-19081	188	10	the	the	DET
bracis-19081	188	11	use	use	NOUN
bracis-19081	188	12	of	of	ADP
bracis-19081	188	13	active	active	ADJ
bracis-19081	188	14	learning	learning	NOUN
bracis-19081	188	15	algorithms	algorithm	NOUN
bracis-19081	188	16	in	in	ADP
bracis-19081	188	17	real	real	ADJ
bracis-19081	188	18	-	-	PUNCT
bracis-19081	188	19	world	world	NOUN
bracis-19081	188	20	low	low	ADJ
bracis-19081	188	21	-	-	PUNCT
bracis-19081	188	22	resource	resource	NOUN
bracis-19081	188	23	scenarios	scenario	NOUN
bracis-19081	188	24	.	.	PUNCT
bracis-19081	189	1	another	another	DET
bracis-19081	189	2	observation	observation	NOUN
bracis-19081	189	3	made	make	VERB
bracis-19081	189	4	is	be	AUX
bracis-19081	189	5	that	that	SCONJ
bracis-19081	189	6	the	the	DET
bracis-19081	189	7	self	self	NOUN
bracis-19081	189	8	-	-	PUNCT
bracis-19081	189	9	training	training	NOUN
bracis-19081	189	10	technique	technique	NOUN
bracis-19081	189	11	employed	employ	VERB
bracis-19081	189	12	here	here	ADV
bracis-19081	189	13	was	be	AUX
bracis-19081	189	14	n’t	not	PART
bracis-19081	189	15	able	able	ADJ
bracis-19081	189	16	to	to	PART
bracis-19081	189	17	improve	improve	VERB
bracis-19081	189	18	the	the	DET
bracis-19081	189	19	model	model	NOUN
bracis-19081	189	20	’s	’s	PART
bracis-19081	189	21	performance	performance	NOUN
bracis-19081	189	22	.	.	PUNCT
bracis-19081	190	1	future	future	ADJ
bracis-19081	190	2	works	work	NOUN
bracis-19081	190	3	may	may	AUX
bracis-19081	190	4	investigate	investigate	VERB
bracis-19081	190	5	more	more	ADV
bracis-19081	190	6	sophisticated	sophisticated	ADJ
bracis-19081	190	7	self	self	NOUN
bracis-19081	190	8	-	-	PUNCT
bracis-19081	190	9	training	training	NOUN
bracis-19081	190	10	techniques	technique	NOUN
bracis-19081	190	11	,	,	PUNCT
bracis-19081	190	12	such	such	ADJ
bracis-19081	190	13	as	as	ADP
bracis-19081	190	14	consistency	consistency	NOUN
bracis-19081	190	15	regularization	regularization	NOUN
bracis-19081	190	16	techniques	technique	NOUN
bracis-19081	190	17	,	,	PUNCT
bracis-19081	190	18	which	which	PRON
bracis-19081	190	19	are	be	AUX
bracis-19081	190	20	often	often	ADV
bracis-19081	190	21	employed	employ	VERB
bracis-19081	190	22	by	by	ADP
bracis-19081	190	23	current	current	ADJ
bracis-19081	190	24	state	state	NOUN
bracis-19081	190	25	-	-	PUNCT
bracis-19081	190	26	of	of	ADP
bracis-19081	190	27	-	-	PUNCT
bracis-19081	190	28	the	the	DET
bracis-19081	190	29	-	-	PUNCT
bracis-19081	190	30	art	art	NOUN
bracis-19081	190	31	semi	semi	ADJ
bracis-19081	190	32	-	-	ADJ
bracis-19081	190	33	supervised	supervised	ADJ
bracis-19081	190	34	methods	method	NOUN
bracis-19081	190	35	[	[	X
bracis-19081	190	36	1	1	NUM
bracis-19081	190	37	]	]	PUNCT
bracis-19081	190	38	.	.	PUNCT
bracis-19081	191	1	these	these	DET
bracis-19081	191	2	more	more	ADV
bracis-19081	191	3	recent	recent	ADJ
bracis-19081	191	4	self	self	NOUN
bracis-19081	191	5	-	-	PUNCT
bracis-19081	191	6	training	training	NOUN
bracis-19081	191	7	techniques	technique	NOUN
bracis-19081	191	8	also	also	ADV
bracis-19081	191	9	tend	tend	VERB
bracis-19081	191	10	to	to	PART
bracis-19081	191	11	use	use	VERB
bracis-19081	191	12	soft	soft	ADJ
bracis-19081	191	13	targets	target	NOUN
bracis-19081	191	14	for	for	ADP
bracis-19081	191	15	training	training	NOUN
bracis-19081	191	16	,	,	PUNCT
bracis-19081	191	17	instead	instead	ADV
bracis-19081	191	18	of	of	ADP
bracis-19081	191	19	hard	hard	ADJ
bracis-19081	191	20	targets	target	NOUN
bracis-19081	191	21	(	(	PUNCT
bracis-19081	191	22	i.e.	i.e.	X
bracis-19081	191	23	one	one	NUM
bracis-19081	191	24	hot	hot	ADJ
bracis-19081	191	25	encoded	encode	VERB
bracis-19081	191	26	vectors	vector	NOUN
bracis-19081	191	27	)	)	PUNCT
bracis-19081	192	1	[	[	X
bracis-19081	192	2	1	1	NUM
bracis-19081	192	3	,	,	PUNCT
bracis-19081	192	4	8	8	NUM
bracis-19081	192	5	]	]	PUNCT
bracis-19081	192	6	,	,	PUNCT
bracis-19081	192	7	in	in	ADP
bracis-19081	192	8	a	a	DET
bracis-19081	192	9	setup	setup	NOUN
bracis-19081	192	10	similar	similar	ADJ
bracis-19081	192	11	to	to	ADP
bracis-19081	192	12	knowledge	knowledge	NOUN
bracis-19081	192	13	distillation	distillation	NOUN
bracis-19081	192	14	[	[	X
bracis-19081	192	15	3	3	NUM
bracis-19081	192	16	]	]	PUNCT
bracis-19081	192	17	.	.	PUNCT
bracis-19081	193	1	notes	note	NOUN
bracis-19081	193	2	1.http://nido.unb.br/.	1.http://nido.unb.br/.	PROPN
bracis-19081	193	3	2.https://avio11.github.io/resources/aposentadoria/.	2.https://avio11.github.io/resources/aposentadoria/.	NUM
bracis-19081	193	4	references	reference	NOUN
bracis-19081	193	5	clark	clark	PROPN
bracis-19081	193	6	,	,	PUNCT
bracis-19081	193	7	k.	k.	PROPN
bracis-19081	193	8	,	,	PUNCT
bracis-19081	193	9	luong	luong	PROPN
bracis-19081	193	10	,	,	PUNCT
bracis-19081	193	11	m.t	m.t	PROPN
bracis-19081	193	12	.	.	PROPN
bracis-19081	193	13	,	,	PUNCT
bracis-19081	193	14	manning	manning	NOUN
bracis-19081	193	15	,	,	PUNCT
bracis-19081	193	16	c.d	c.d	PROPN
bracis-19081	193	17	.	.	PROPN
bracis-19081	193	18	,	,	PUNCT
bracis-19081	193	19	le	le	PROPN
bracis-19081	193	20	,	,	PUNCT
bracis-19081	193	21	q.	q.	PROPN
bracis-19081	193	22	:	:	PUNCT
bracis-19081	193	23	semi	semi	ADJ
bracis-19081	193	24	-	-	ADJ
bracis-19081	193	25	supervised	supervised	ADJ
bracis-19081	193	26	sequence	sequence	NOUN
bracis-19081	193	27	modeling	modeling	NOUN
bracis-19081	193	28	with	with	ADP
bracis-19081	193	29	cross	cross	ADJ
bracis-19081	193	30	-	-	ADJ
bracis-19081	193	31	view	view	ADJ
bracis-19081	193	32	training	training	NOUN
bracis-19081	193	33	.	.	PUNCT
bracis-19081	194	1	in	in	ADP
bracis-19081	194	2	:	:	PUNCT
bracis-19081	194	3	proceedings	proceeding	NOUN
bracis-19081	194	4	of	of	ADP
bracis-19081	194	5	the	the	DET
bracis-19081	194	6	2018	2018	NUM
bracis-19081	194	7	conference	conference	NOUN
bracis-19081	194	8	on	on	ADP
bracis-19081	194	9	empirical	empirical	ADJ
bracis-19081	194	10	methods	method	NOUN
bracis-19081	194	11	in	in	ADP
bracis-19081	194	12	natural	natural	ADJ
bracis-19081	194	13	language	language	NOUN
bracis-19081	194	14	processing	processing	NOUN
bracis-19081	194	15	,	,	PUNCT
bracis-19081	194	16	pp	pp	ADJ
bracis-19081	194	17	.	.	PUNCT
bracis-19081	194	18	1914–1925	1914–1925	NUM
bracis-19081	194	19	.	.	PUNCT
bracis-19081	194	20	association	association	NOUN
bracis-19081	194	21	for	for	ADP
bracis-19081	194	22	computational	computational	ADJ
bracis-19081	194	23	linguistics	linguistic	NOUN
bracis-19081	194	24	,	,	PUNCT
bracis-19081	194	25	brussels	brussels	PROPN
bracis-19081	194	26	,	,	PUNCT
bracis-19081	194	27	october	october	PROPN
bracis-19081	194	28	–	–	PUNCT
bracis-19081	194	29	november	november	PROPN
bracis-19081	194	30	2018	2018	NUM
bracis-19081	194	31	.	.	PUNCT
bracis-19081	195	1	https://doi.org/10.18653/v1/d18-1217	https://doi.org/10.18653/v1/d18-1217	PROPN
bracis-19081	195	2	hartmann	hartmann	PROPN
bracis-19081	195	3	,	,	PUNCT
bracis-19081	195	4	n.s	n.s	PROPN
bracis-19081	195	5	.	.	PROPN
bracis-19081	195	6	,	,	PUNCT
bracis-19081	195	7	fonseca	fonseca	PROPN
bracis-19081	195	8	,	,	PUNCT
bracis-19081	195	9	e.r	e.r	PROPN
bracis-19081	195	10	.	.	PROPN
bracis-19081	195	11	,	,	PUNCT
bracis-19081	195	12	shulby	shulby	PROPN
bracis-19081	195	13	,	,	PUNCT
bracis-19081	195	14	c.d	c.d	PROPN
bracis-19081	195	15	.	.	PROPN
bracis-19081	195	16	,	,	PUNCT
bracis-19081	195	17	treviso	treviso	PROPN
bracis-19081	195	18	,	,	PUNCT
bracis-19081	195	19	m.v	m.v	PROPN
bracis-19081	195	20	.	.	PROPN
bracis-19081	195	21	,	,	PUNCT
bracis-19081	195	22	rodrigues	rodrigues	PROPN
bracis-19081	195	23	,	,	PUNCT
bracis-19081	195	24	j.s	j.s	PROPN
bracis-19081	195	25	.	.	PROPN
bracis-19081	195	26	,	,	PUNCT
bracis-19081	195	27	aluísio	aluísio	PROPN
bracis-19081	195	28	,	,	PUNCT
bracis-19081	195	29	s.m	s.m	PROPN
bracis-19081	195	30	.	.	PROPN
bracis-19081	195	31	:	:	PUNCT
bracis-19081	196	1	portuguese	portuguese	ADJ
bracis-19081	196	2	word	word	NOUN
bracis-19081	196	3	embeddings	embedding	NOUN
bracis-19081	196	4	:	:	PUNCT
bracis-19081	196	5	evaluating	evaluate	VERB
bracis-19081	196	6	on	on	ADP
bracis-19081	196	7	word	word	NOUN
bracis-19081	196	8	analogies	analogy	NOUN
bracis-19081	196	9	and	and	CCONJ
bracis-19081	196	10	natural	natural	ADJ
bracis-19081	196	11	language	language	NOUN
bracis-19081	196	12	tasks	task	NOUN
bracis-19081	196	13	.	.	PUNCT
bracis-19081	197	1	in	in	ADP
bracis-19081	197	2	:	:	PUNCT
bracis-19081	197	3	anais	anais	PROPN
bracis-19081	197	4	do	do	AUX
bracis-19081	197	5	xi	xi	PROPN
bracis-19081	197	6	simpósio	simpósio	VERB
bracis-19081	197	7	brasileiro	brasileiro	PROPN
bracis-19081	197	8	de	de	PROPN
bracis-19081	197	9	tecnologia	tecnologia	PROPN
bracis-19081	197	10	da	da	PROPN
bracis-19081	197	11	informação	informação	PROPN
bracis-19081	197	12	e	e	PROPN
bracis-19081	197	13	da	da	PROPN
bracis-19081	197	14	linguagem	linguagem	PROPN
bracis-19081	197	15	humana	humana	PROPN
bracis-19081	197	16	,	,	PUNCT
bracis-19081	197	17	pp	pp	ADJ
bracis-19081	197	18	.	.	PUNCT
bracis-19081	198	1	122–131	122–131	NUM
bracis-19081	198	2	.	.	PUNCT
bracis-19081	199	1	sbc	sbc	PROPN
bracis-19081	199	2	,	,	PUNCT
bracis-19081	199	3	porto	porto	PROPN
bracis-19081	199	4	alegre	alegre	PROPN
bracis-19081	199	5	,	,	PUNCT
bracis-19081	199	6	rs	rs	NOUN
bracis-19081	199	7	,	,	PUNCT
bracis-19081	199	8	brasil	brasil	NOUN
bracis-19081	199	9	(	(	PUNCT
bracis-19081	199	10	2017	2017	NUM
bracis-19081	199	11	)	)	PUNCT
bracis-19081	199	12	.	.	PUNCT
bracis-19081	200	1	https://sol.sbc.org.br/index.php/stil/article/view/4008	https://sol.sbc.org.br/index.php/stil/article/view/4008	PROPN
bracis-19081	200	2	hinton	hinton	PROPN
bracis-19081	200	3	,	,	PUNCT
bracis-19081	200	4	g.	g.	PROPN
bracis-19081	200	5	,	,	PUNCT
bracis-19081	200	6	vinyals	vinyal	NOUN
bracis-19081	200	7	,	,	PUNCT
bracis-19081	200	8	o.	o.	PROPN
bracis-19081	200	9	,	,	PUNCT
bracis-19081	200	10	dean	dean	PROPN
bracis-19081	200	11	,	,	PUNCT
bracis-19081	200	12	j.	j.	PROPN
bracis-19081	200	13	:	:	PUNCT
bracis-19081	200	14	distilling	distil	VERB
bracis-19081	200	15	the	the	DET
bracis-19081	200	16	knowledge	knowledge	NOUN
bracis-19081	200	17	in	in	ADP
bracis-19081	200	18	a	a	DET
bracis-19081	200	19	neural	neural	ADJ
bracis-19081	200	20	network	network	NOUN
bracis-19081	200	21	(	(	PUNCT
bracis-19081	200	22	2015	2015	NUM
bracis-19081	200	23	)	)	PUNCT
bracis-19081	200	24	google	google	PROPN
bracis-19081	200	25	scholar	scholar	NOUN
bracis-19081	200	26	  	  	SPACE
bracis-19081	200	27	houlsby	houlsby	ADJ
bracis-19081	200	28	,	,	PUNCT
bracis-19081	200	29	n.	n.	NOUN
bracis-19081	200	30	,	,	PUNCT
bracis-19081	200	31	huszár	huszár	NOUN
bracis-19081	200	32	,	,	PUNCT
bracis-19081	200	33	f.	f.	PROPN
bracis-19081	200	34	,	,	PUNCT
bracis-19081	200	35	ghahramani	ghahramani	PROPN
bracis-19081	200	36	,	,	PUNCT
bracis-19081	200	37	z.	z.	PROPN
bracis-19081	200	38	,	,	PUNCT
bracis-19081	200	39	lengyel	lengyel	PROPN
bracis-19081	200	40	,	,	PUNCT
bracis-19081	200	41	m.	m.	NOUN
bracis-19081	200	42	:	:	PUNCT
bracis-19081	200	43	bayesian	bayesian	NOUN
bracis-19081	200	44	active	active	ADJ
bracis-19081	200	45	learning	learning	NOUN
bracis-19081	200	46	for	for	ADP
bracis-19081	200	47	classification	classification	NOUN
bracis-19081	200	48	and	and	CCONJ
bracis-19081	200	49	preference	preference	NOUN
bracis-19081	200	50	learning	learning	NOUN
bracis-19081	200	51	(	(	PUNCT
bracis-19081	200	52	2011	2011	NUM
bracis-19081	200	53	)	)	PUNCT
bracis-19081	200	54	google	google	PROPN
bracis-19081	200	55	scholar	scholar	NOUN
bracis-19081	200	56	  	  	SPACE
bracis-19081	200	57	lample	lample	PROPN
bracis-19081	200	58	,	,	PUNCT
bracis-19081	200	59	g.	g.	PROPN
bracis-19081	200	60	,	,	PUNCT
bracis-19081	200	61	ballesteros	ballesteros	PROPN
bracis-19081	200	62	,	,	PUNCT
bracis-19081	200	63	m.	m.	NOUN
bracis-19081	200	64	,	,	PUNCT
bracis-19081	200	65	subramanian	subramanian	PROPN
bracis-19081	200	66	,	,	PUNCT
bracis-19081	200	67	s.	s.	PROPN
bracis-19081	200	68	,	,	PUNCT
bracis-19081	200	69	kawakami	kawakami	PROPN
bracis-19081	200	70	,	,	PUNCT
bracis-19081	200	71	k.	k.	PROPN
bracis-19081	200	72	,	,	PUNCT
bracis-19081	200	73	dyer	dyer	PROPN
bracis-19081	200	74	,	,	PUNCT
bracis-19081	200	75	c.	c.	PROPN
bracis-19081	200	76	:	:	PUNCT
bracis-19081	200	77	neural	neural	ADJ
bracis-19081	200	78	architectures	architecture	NOUN
bracis-19081	200	79	for	for	ADP
bracis-19081	200	80	named	name	VERB
bracis-19081	200	81	entity	entity	NOUN
bracis-19081	200	82	recognition	recognition	NOUN
bracis-19081	200	83	.	.	PUNCT
bracis-19081	201	1	in	in	ADP
bracis-19081	201	2	:	:	PUNCT
bracis-19081	201	3	proceedings	proceeding	NOUN
bracis-19081	201	4	of	of	ADP
bracis-19081	201	5	the	the	DET
bracis-19081	201	6	2016	2016	NUM
bracis-19081	201	7	conference	conference	NOUN
bracis-19081	201	8	of	of	ADP
bracis-19081	201	9	the	the	DET
bracis-19081	201	10	north	north	ADJ
bracis-19081	201	11	american	american	ADJ
bracis-19081	201	12	chapter	chapter	NOUN
bracis-19081	201	13	of	of	ADP
bracis-19081	201	14	the	the	DET
bracis-19081	201	15	association	association	NOUN
bracis-19081	201	16	for	for	ADP
bracis-19081	201	17	computational	computational	ADJ
bracis-19081	201	18	linguistics	linguistic	NOUN
bracis-19081	201	19	:	:	PUNCT
bracis-19081	201	20	human	human	ADJ
bracis-19081	201	21	language	language	NOUN
bracis-19081	201	22	technologies	technology	NOUN
bracis-19081	201	23	,	,	PUNCT
bracis-19081	201	24	pp	pp	ADJ
bracis-19081	201	25	.	.	PUNCT
bracis-19081	202	1	260–270	260–270	NUM
bracis-19081	202	2	.	.	PUNCT
bracis-19081	202	3	association	association	NOUN
bracis-19081	202	4	for	for	ADP
bracis-19081	202	5	computational	computational	ADJ
bracis-19081	202	6	linguistics	linguistic	NOUN
bracis-19081	202	7	,	,	PUNCT
bracis-19081	202	8	san	san	PROPN
bracis-19081	202	9	diego	diego	PROPN
bracis-19081	202	10	,	,	PUNCT
bracis-19081	202	11	june	june	PROPN
bracis-19081	202	12	2016	2016	NUM
bracis-19081	202	13	.	.	PUNCT
bracis-19081	203	1	https://doi.org/10.18653/v1/n16-1030	https://doi.org/10.18653/v1/n16-1030	PROPN
bracis-19081	203	2	,	,	PUNCT
bracis-19081	203	3	https://www.aclweb.org/anthology/n16-1030	https://www.aclweb.org/anthology/n16-1030	PUNCT
bracis-19081	203	4	lin	lin	PROPN
bracis-19081	203	5	,	,	PUNCT
bracis-19081	203	6	y.	y.	PROPN
bracis-19081	203	7	,	,	PUNCT
bracis-19081	203	8	sun	sun	PROPN
bracis-19081	203	9	,	,	PUNCT
bracis-19081	203	10	c.	c.	PROPN
bracis-19081	203	11	,	,	PUNCT
bracis-19081	203	12	xiaolong	xiaolong	PROPN
bracis-19081	203	13	,	,	PUNCT
bracis-19081	203	14	w.	w.	PROPN
bracis-19081	203	15	,	,	PUNCT
bracis-19081	203	16	xuan	xuan	PROPN
bracis-19081	203	17	,	,	PUNCT
bracis-19081	203	18	w.	w.	PROPN
bracis-19081	203	19	:	:	PUNCT
bracis-19081	203	20	combining	combine	VERB
bracis-19081	203	21	self	self	NOUN
bracis-19081	203	22	learning	learning	NOUN
bracis-19081	203	23	and	and	CCONJ
bracis-19081	203	24	active	active	ADJ
bracis-19081	203	25	learning	learning	NOUN
bracis-19081	203	26	for	for	ADP
bracis-19081	203	27	chinese	chinese	ADJ
bracis-19081	203	28	named	name	VERB
bracis-19081	203	29	entity	entity	NOUN
bracis-19081	203	30	recognition	recognition	NOUN
bracis-19081	203	31	.	.	PUNCT
bracis-19081	204	1	j.	j.	PROPN
bracis-19081	204	2	softw	softw	PROPN
bracis-19081	204	3	.	.	PROPN
bracis-19081	205	1	5	5	NUM
bracis-19081	205	2	,	,	PUNCT
bracis-19081	205	3	may	may	AUX
bracis-19081	205	4	2010	2010	NUM
bracis-19081	205	5	.	.	PUNCT
bracis-19081	206	1	https://doi.org/10.4304/jsw.5.5.530-537	https://doi.org/10.4304/jsw.5.5.530-537	PROPN
bracis-19081	206	2	ma	ma	PROPN
bracis-19081	206	3	,	,	PUNCT
bracis-19081	206	4	x.	x.	NOUN
bracis-19081	206	5	,	,	PUNCT
bracis-19081	206	6	hovy	hovy	PROPN
bracis-19081	206	7	,	,	PUNCT
bracis-19081	206	8	e.	e.	PROPN
bracis-19081	206	9	:	:	PUNCT
bracis-19081	206	10	end	end	VERB
bracis-19081	206	11	-	-	PUNCT
bracis-19081	206	12	to	to	ADP
bracis-19081	206	13	-	-	PUNCT
bracis-19081	206	14	end	end	NOUN
bracis-19081	206	15	sequence	sequence	NOUN
bracis-19081	206	16	labeling	labeling	NOUN
bracis-19081	206	17	via	via	ADP
bracis-19081	206	18	bi	bi	ADJ
bracis-19081	206	19	-	-	ADJ
bracis-19081	206	20	directional	directional	ADJ
bracis-19081	206	21	lstm	lstm	ADJ
bracis-19081	206	22	-	-	PUNCT
bracis-19081	206	23	cnns	cnns	PROPN
bracis-19081	206	24	-	-	PUNCT
bracis-19081	206	25	crf	crf	NOUN
bracis-19081	206	26	.	.	PUNCT
bracis-19081	207	1	in	in	ADP
bracis-19081	207	2	:	:	PUNCT
bracis-19081	207	3	proceedings	proceeding	NOUN
bracis-19081	207	4	of	of	ADP
bracis-19081	207	5	the	the	DET
bracis-19081	207	6	54th	54th	ADJ
bracis-19081	207	7	annual	annual	ADJ
bracis-19081	207	8	meeting	meeting	NOUN
bracis-19081	207	9	of	of	ADP
bracis-19081	207	10	the	the	DET
bracis-19081	207	11	association	association	NOUN
bracis-19081	207	12	for	for	ADP
bracis-19081	207	13	computational	computational	ADJ
bracis-19081	207	14	linguistics	linguistic	NOUN
bracis-19081	207	15	(	(	PUNCT
bracis-19081	207	16	volume	volume	NOUN
bracis-19081	207	17	1	1	NUM
bracis-19081	207	18	:	:	PUNCT
bracis-19081	207	19	long	long	ADJ
bracis-19081	207	20	papers	paper	NOUN
bracis-19081	207	21	)	)	PUNCT
bracis-19081	207	22	,	,	PUNCT
bracis-19081	207	23	pp	pp	ADP
bracis-19081	207	24	.	.	PUNCT
bracis-19081	208	1	1064–1074	1064–1074	NUM
bracis-19081	208	2	.	.	PUNCT
bracis-19081	209	1	association	association	NOUN
bracis-19081	209	2	for	for	ADP
bracis-19081	209	3	computational	computational	ADJ
bracis-19081	209	4	linguistics	linguistic	NOUN
bracis-19081	209	5	,	,	PUNCT
bracis-19081	209	6	berlin	berlin	PROPN
bracis-19081	209	7	,	,	PUNCT
bracis-19081	209	8	august	august	PROPN
bracis-19081	209	9	2016	2016	NUM
bracis-19081	209	10	.	.	PUNCT
bracis-19081	210	1	https://doi.org/10.18653/v1/p16-1101	https://doi.org/10.18653/v1/p16-1101	PROPN
bracis-19081	210	2	miyato	miyato	PROPN
bracis-19081	210	3	,	,	PUNCT
bracis-19081	210	4	t.	t.	PROPN
bracis-19081	210	5	,	,	PUNCT
bracis-19081	210	6	dai	dai	PROPN
bracis-19081	210	7	,	,	PUNCT
bracis-19081	210	8	a.m.	a.m.	ADV
bracis-19081	210	9	,	,	PUNCT
bracis-19081	210	10	goodfellow	goodfellow	PROPN
bracis-19081	210	11	,	,	PUNCT
bracis-19081	210	12	i.	i.	NOUN
bracis-19081	210	13	:	:	PUNCT
bracis-19081	210	14	adversarial	adversarial	ADJ
bracis-19081	210	15	training	training	NOUN
bracis-19081	210	16	methods	method	NOUN
bracis-19081	210	17	for	for	ADP
bracis-19081	210	18	semi	semi	ADJ
bracis-19081	210	19	-	-	ADJ
bracis-19081	210	20	supervised	supervised	ADJ
bracis-19081	210	21	text	text	NOUN
bracis-19081	210	22	classification	classification	NOUN
bracis-19081	210	23	.	.	PUNCT
bracis-19081	211	1	in	in	ADP
bracis-19081	211	2	:	:	PUNCT
bracis-19081	211	3	international	international	ADJ
bracis-19081	211	4	conference	conference	NOUN
bracis-19081	211	5	on	on	ADP
bracis-19081	211	6	learning	learn	VERB
bracis-19081	211	7	representations	representation	NOUN
bracis-19081	211	8	(	(	PUNCT
bracis-19081	211	9	iclr	iclr	NOUN
bracis-19081	211	10	)	)	PUNCT
bracis-19081	211	11	(	(	PUNCT
bracis-19081	211	12	2017	2017	NUM
bracis-19081	211	13	)	)	PUNCT
bracis-19081	211	14	google	google	NOUN
bracis-19081	211	15	scholar	scholar	NOUN
bracis-19081	211	16	  	  	SPACE
bracis-19081	211	17	paszke	paszke	NOUN
bracis-19081	211	18	,	,	PUNCT
bracis-19081	211	19	a.	a.	NOUN
bracis-19081	211	20	,	,	PUNCT
bracis-19081	211	21	et	et	PROPN
bracis-19081	211	22	al	al	PROPN
bracis-19081	211	23	.	.	PUNCT
bracis-19081	211	24	:	:	PUNCT
bracis-19081	211	25	pytorch	pytorch	NOUN
bracis-19081	211	26	:	:	PUNCT
bracis-19081	211	27	an	an	DET
bracis-19081	211	28	imperative	imperative	ADJ
bracis-19081	211	29	style	style	NOUN
bracis-19081	211	30	,	,	PUNCT
bracis-19081	211	31	high	high	ADJ
bracis-19081	211	32	-	-	PUNCT
bracis-19081	211	33	performance	performance	NOUN
bracis-19081	211	34	deep	deep	ADJ
bracis-19081	211	35	learning	learning	NOUN
bracis-19081	211	36	library	library	NOUN
bracis-19081	211	37	.	.	PUNCT
bracis-19081	212	1	in	in	ADP
bracis-19081	212	2	:	:	PUNCT
bracis-19081	212	3	wallach	wallach	PROPN
bracis-19081	212	4	,	,	PUNCT
bracis-19081	212	5	h.	h.	PROPN
bracis-19081	212	6	,	,	PUNCT
bracis-19081	212	7	larochelle	larochelle	PROPN
bracis-19081	212	8	,	,	PUNCT
bracis-19081	212	9	h.	h.	PROPN
bracis-19081	212	10	,	,	PUNCT
bracis-19081	212	11	beygelzimer	beygelzimer	NOUN
bracis-19081	212	12	,	,	PUNCT
bracis-19081	212	13	a.	a.	NOUN
bracis-19081	212	14	,	,	PUNCT
bracis-19081	212	15	d’alché	d’alché	NOUN
bracis-19081	212	16	-	-	PUNCT
bracis-19081	212	17	buc	buc	PROPN
bracis-19081	212	18	,	,	PUNCT
bracis-19081	212	19	f.	f.	PROPN
bracis-19081	212	20	,	,	PUNCT
bracis-19081	212	21	fox	fox	PROPN
bracis-19081	212	22	,	,	PUNCT
bracis-19081	212	23	e.	e.	PROPN
bracis-19081	212	24	,	,	PUNCT
bracis-19081	212	25	garnett	garnett	PROPN
bracis-19081	212	26	,	,	PUNCT
bracis-19081	212	27	r.	r.	PROPN
bracis-19081	212	28	(	(	PUNCT
bracis-19081	212	29	eds	eds	PROPN
bracis-19081	212	30	.	.	PUNCT
bracis-19081	212	31	)	)	PUNCT
bracis-19081	212	32	advances	advance	NOUN
bracis-19081	212	33	in	in	ADP
bracis-19081	212	34	neural	neural	ADJ
bracis-19081	212	35	information	information	NOUN
bracis-19081	212	36	processing	processing	NOUN
bracis-19081	212	37	systems	system	NOUN
bracis-19081	212	38	32	32	NUM
bracis-19081	212	39	,	,	PUNCT
bracis-19081	212	40	pp	pp	ADJ
bracis-19081	212	41	.	.	PUNCT
bracis-19081	213	1	8024–8035	8024–8035	NUM
bracis-19081	213	2	.	.	PUNCT
bracis-19081	214	1	curran	curran	PROPN
bracis-19081	214	2	associates	associates	PROPN
bracis-19081	214	3	,	,	PUNCT
bracis-19081	214	4	inc	inc	PROPN
bracis-19081	214	5	.	.	PROPN
bracis-19081	214	6	(	(	PUNCT
bracis-19081	214	7	2019	2019	NUM
bracis-19081	214	8	)	)	PUNCT
bracis-19081	214	9	.	.	PUNCT
bracis-19081	215	1	http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf	http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf	PROPN
bracis-19081	215	2	pennington	pennington	PROPN
bracis-19081	215	3	,	,	PUNCT
bracis-19081	215	4	j.	j.	PROPN
bracis-19081	215	5	,	,	PUNCT
bracis-19081	215	6	socher	socher	PROPN
bracis-19081	215	7	,	,	PUNCT
bracis-19081	215	8	r.	r.	PROPN
bracis-19081	215	9	,	,	PUNCT
bracis-19081	215	10	manning	manning	NOUN
bracis-19081	215	11	,	,	PUNCT
bracis-19081	215	12	c.	c.	NOUN
bracis-19081	215	13	:	:	PUNCT
bracis-19081	215	14	glove	glove	NOUN
bracis-19081	215	15	:	:	PUNCT
bracis-19081	215	16	global	global	ADJ
bracis-19081	215	17	vectors	vector	NOUN
bracis-19081	215	18	for	for	ADP
bracis-19081	215	19	word	word	NOUN
bracis-19081	215	20	representation	representation	NOUN
bracis-19081	215	21	.	.	PUNCT
bracis-19081	216	1	in	in	ADP
bracis-19081	216	2	:	:	PUNCT
bracis-19081	216	3	proceedings	proceeding	NOUN
bracis-19081	216	4	of	of	ADP
bracis-19081	216	5	the	the	DET
bracis-19081	216	6	2014	2014	NUM
bracis-19081	216	7	conference	conference	NOUN
bracis-19081	216	8	on	on	ADP
bracis-19081	216	9	empirical	empirical	ADJ
bracis-19081	216	10	methods	method	NOUN
bracis-19081	216	11	in	in	ADP
bracis-19081	216	12	natural	natural	ADJ
bracis-19081	216	13	language	language	NOUN
bracis-19081	216	14	processing	processing	NOUN
bracis-19081	216	15	(	(	PUNCT
bracis-19081	216	16	emnlp	emnlp	ADJ
bracis-19081	216	17	)	)	PUNCT
bracis-19081	216	18	,	,	PUNCT
bracis-19081	216	19	pp	pp	PROPN
bracis-19081	216	20	.	.	PUNCT
bracis-19081	216	21	1532–1543	1532–1543	NUM
bracis-19081	216	22	.	.	PUNCT
bracis-19081	216	23	association	association	NOUN
bracis-19081	216	24	for	for	ADP
bracis-19081	216	25	computational	computational	ADJ
bracis-19081	216	26	linguistics	linguistic	NOUN
bracis-19081	216	27	,	,	PUNCT
bracis-19081	216	28	october	october	PROPN
bracis-19081	216	29	2014	2014	NUM
bracis-19081	216	30	.	.	PUNCT
bracis-19081	217	1	https://doi.org/10.3115/v1/d14-1162	https://doi.org/10.3115/v1/d14-1162	NOUN
bracis-19081	217	2	pradhan	pradhan	PROPN
bracis-19081	217	3	,	,	PUNCT
bracis-19081	217	4	s.	s.	PROPN
bracis-19081	217	5	,	,	PUNCT
bracis-19081	217	6	et	et	PROPN
bracis-19081	217	7	al	al	PROPN
bracis-19081	217	8	.	.	PROPN
bracis-19081	217	9	:	:	PUNCT
bracis-19081	218	1	towards	towards	ADP
bracis-19081	218	2	robust	robust	ADJ
bracis-19081	218	3	linguistic	linguistic	ADJ
bracis-19081	218	4	analysis	analysis	NOUN
bracis-19081	218	5	using	use	VERB
bracis-19081	218	6	ontonotes	ontonote	NOUN
bracis-19081	218	7	.	.	PUNCT
bracis-19081	219	1	in	in	ADP
bracis-19081	219	2	:	:	PUNCT
bracis-19081	219	3	proceedings	proceeding	NOUN
bracis-19081	219	4	of	of	ADP
bracis-19081	219	5	the	the	DET
bracis-19081	219	6	seventeenth	seventeenth	ADJ
bracis-19081	219	7	conference	conference	NOUN
bracis-19081	219	8	on	on	ADP
bracis-19081	219	9	computational	computational	ADJ
bracis-19081	219	10	natural	natural	ADJ
bracis-19081	219	11	language	language	NOUN
bracis-19081	219	12	learning	learning	NOUN
bracis-19081	219	13	,	,	PUNCT
bracis-19081	219	14	pp	pp	ADP
bracis-19081	219	15	.	.	PUNCT
bracis-19081	220	1	143–152	143–152	NUM
bracis-19081	220	2	.	.	PUNCT
bracis-19081	220	3	association	association	NOUN
bracis-19081	220	4	for	for	ADP
bracis-19081	220	5	computational	computational	ADJ
bracis-19081	220	6	linguistics	linguistic	NOUN
bracis-19081	220	7	,	,	PUNCT
bracis-19081	220	8	sofia	sofia	PROPN
bracis-19081	220	9	,	,	PUNCT
bracis-19081	220	10	august	august	PROPN
bracis-19081	220	11	2013	2013	NUM
bracis-19081	220	12	google	google	PROPN
bracis-19081	220	13	scholar	scholar	NOUN
bracis-19081	220	14	  	  	SPACE
bracis-19081	220	15	ratinov	ratinov	NOUN
bracis-19081	220	16	,	,	PUNCT
bracis-19081	220	17	l.	l.	PROPN
bracis-19081	220	18	,	,	PUNCT
bracis-19081	220	19	roth	roth	PROPN
bracis-19081	220	20	,	,	PUNCT
bracis-19081	220	21	d.	d.	PROPN
bracis-19081	220	22	:	:	PUNCT
bracis-19081	220	23	design	design	NOUN
bracis-19081	220	24	challenges	challenge	NOUN
bracis-19081	220	25	and	and	CCONJ
bracis-19081	220	26	misconceptions	misconception	NOUN
bracis-19081	220	27	in	in	ADP
bracis-19081	220	28	named	name	VERB
bracis-19081	220	29	entity	entity	NOUN
bracis-19081	220	30	recognition	recognition	NOUN
bracis-19081	220	31	.	.	PUNCT
bracis-19081	221	1	in	in	ADP
bracis-19081	221	2	:	:	PUNCT
bracis-19081	221	3	proceedings	proceeding	NOUN
bracis-19081	221	4	of	of	ADP
bracis-19081	221	5	the	the	DET
bracis-19081	221	6	thirteenth	thirteenth	ADJ
bracis-19081	221	7	conference	conference	NOUN
bracis-19081	221	8	on	on	ADP
bracis-19081	221	9	computational	computational	ADJ
bracis-19081	221	10	natural	natural	ADJ
bracis-19081	221	11	language	language	NOUN
bracis-19081	221	12	learning	learning	NOUN
bracis-19081	221	13	(	(	PUNCT
bracis-19081	221	14	conll-2009	conll-2009	ADJ
bracis-19081	221	15	)	)	PUNCT
bracis-19081	221	16	,	,	PUNCT
bracis-19081	221	17	pp	pp	ADJ
bracis-19081	221	18	.	.	PUNCT
bracis-19081	222	1	147–155	147–155	NUM
bracis-19081	222	2	.	.	PUNCT
bracis-19081	222	3	association	association	NOUN
bracis-19081	222	4	for	for	ADP
bracis-19081	222	5	computational	computational	ADJ
bracis-19081	222	6	linguistics	linguistic	NOUN
bracis-19081	222	7	,	,	PUNCT
bracis-19081	222	8	boulder	boulder	NOUN
bracis-19081	222	9	,	,	PUNCT
bracis-19081	222	10	june	june	PROPN
bracis-19081	222	11	2009	2009	NUM
bracis-19081	222	12	.	.	PUNCT
bracis-19081	223	1	https://www.aclweb.org/anthology/w09-1119	https://www.aclweb.org/anthology/w09-1119	X
bracis-19081	223	2	sang	sing	VERB
bracis-19081	223	3	,	,	PUNCT
bracis-19081	223	4	e.f.t.k	e.f.t.k	PROPN
bracis-19081	223	5	.	.	PROPN
bracis-19081	223	6	,	,	PUNCT
bracis-19081	223	7	meulder	meulder	NOUN
bracis-19081	223	8	,	,	PUNCT
bracis-19081	223	9	f.d	f.d	PROPN
bracis-19081	223	10	.	.	PUNCT
bracis-19081	223	11	:	:	PUNCT
bracis-19081	224	1	introduction	introduction	NOUN
bracis-19081	224	2	to	to	ADP
bracis-19081	224	3	the	the	DET
bracis-19081	224	4	conll-2003	conll-2003	NOUN
bracis-19081	224	5	shared	share	VERB
bracis-19081	224	6	task	task	NOUN
bracis-19081	224	7	:	:	PUNCT
bracis-19081	224	8	language	language	NOUN
bracis-19081	224	9	-	-	PUNCT
bracis-19081	224	10	independent	independent	NOUN
bracis-19081	224	11	named	name	VERB
bracis-19081	224	12	entity	entity	NOUN
bracis-19081	224	13	recognition	recognition	NOUN
bracis-19081	224	14	.	.	PUNCT
bracis-19081	225	1	in	in	ADP
bracis-19081	225	2	:	:	PUNCT
bracis-19081	225	3	proceedings	proceeding	NOUN
bracis-19081	225	4	of	of	ADP
bracis-19081	225	5	the	the	DET
bracis-19081	225	6	seventh	seventh	ADJ
bracis-19081	225	7	conference	conference	NOUN
bracis-19081	225	8	on	on	ADP
bracis-19081	225	9	natural	natural	ADJ
bracis-19081	225	10	language	language	NOUN
bracis-19081	225	11	learning	learning	NOUN
bracis-19081	225	12	at	at	ADP
bracis-19081	225	13	hlt	hlt	PROPN
bracis-19081	225	14	-	-	PUNCT
bracis-19081	225	15	naacl	naacl	PROPN
bracis-19081	225	16	2003	2003	NUM
bracis-19081	225	17	,	,	PUNCT
bracis-19081	225	18	pp	pp	ADP
bracis-19081	225	19	.	.	PUNCT
bracis-19081	226	1	142–147	142–147	NUM
bracis-19081	226	2	(	(	PUNCT
bracis-19081	226	3	2003	2003	NUM
bracis-19081	226	4	)	)	PUNCT
bracis-19081	226	5	google	google	PROPN
bracis-19081	226	6	scholar	scholar	NOUN
bracis-19081	226	7	  	  	SPACE
bracis-19081	226	8	settles	settle	NOUN
bracis-19081	226	9	,	,	PUNCT
bracis-19081	226	10	b.	b.	PROPN
bracis-19081	226	11	,	,	PUNCT
bracis-19081	226	12	craven	craven	NOUN
bracis-19081	226	13	,	,	PUNCT
bracis-19081	226	14	m.	m.	NOUN
bracis-19081	226	15	:	:	PUNCT
bracis-19081	226	16	an	an	DET
bracis-19081	226	17	analysis	analysis	NOUN
bracis-19081	226	18	of	of	ADP
bracis-19081	226	19	active	active	ADJ
bracis-19081	226	20	learning	learning	NOUN
bracis-19081	226	21	strategies	strategy	NOUN
bracis-19081	226	22	for	for	ADP
bracis-19081	226	23	sequence	sequence	NOUN
bracis-19081	226	24	labeling	labeling	NOUN
bracis-19081	226	25	tasks	task	NOUN
bracis-19081	226	26	.	.	PUNCT
bracis-19081	227	1	in	in	ADP
bracis-19081	227	2	:	:	PUNCT
bracis-19081	227	3	proceedings	proceeding	NOUN
bracis-19081	227	4	of	of	ADP
bracis-19081	227	5	the	the	DET
bracis-19081	227	6	conference	conference	NOUN
bracis-19081	227	7	on	on	ADP
bracis-19081	227	8	empirical	empirical	ADJ
bracis-19081	227	9	methods	method	NOUN
bracis-19081	227	10	in	in	ADP
bracis-19081	227	11	natural	natural	ADJ
bracis-19081	227	12	language	language	NOUN
bracis-19081	227	13	processing	processing	NOUN
bracis-19081	227	14	,	,	PUNCT
bracis-19081	227	15	emnlp	emnlp	ADP
bracis-19081	227	16	2008	2008	NUM
bracis-19081	227	17	,	,	PUNCT
bracis-19081	227	18	pp	pp	ADJ
bracis-19081	227	19	.	.	PUNCT
bracis-19081	227	20	1070–1079	1070–1079	NUM
bracis-19081	227	21	.	.	PUNCT
bracis-19081	227	22	association	association	NOUN
bracis-19081	227	23	for	for	ADP
bracis-19081	227	24	computational	computational	ADJ
bracis-19081	227	25	linguistics	linguistic	NOUN
bracis-19081	227	26	,	,	PUNCT
bracis-19081	227	27	usa	usa	PROPN
bracis-19081	227	28	(	(	PUNCT
bracis-19081	227	29	2008	2008	NUM
bracis-19081	227	30	)	)	PUNCT
bracis-19081	227	31	google	google	PROPN
bracis-19081	227	32	scholar	scholar	NOUN
bracis-19081	227	33	  	  	SPACE
bracis-19081	227	34	shen	shen	NOUN
bracis-19081	227	35	,	,	PUNCT
bracis-19081	227	36	y.	y.	PROPN
bracis-19081	227	37	,	,	PUNCT
bracis-19081	227	38	yun	yun	PROPN
bracis-19081	227	39	,	,	PUNCT
bracis-19081	227	40	h.	h.	PROPN
bracis-19081	227	41	,	,	PUNCT
bracis-19081	227	42	lipton	lipton	PROPN
bracis-19081	227	43	,	,	PUNCT
bracis-19081	227	44	z.	z.	PROPN
bracis-19081	227	45	,	,	PUNCT
bracis-19081	227	46	kronrod	kronrod	PROPN
bracis-19081	227	47	,	,	PUNCT
bracis-19081	227	48	y.	y.	PROPN
bracis-19081	227	49	,	,	PUNCT
bracis-19081	227	50	anandkumar	anandkumar	PROPN
bracis-19081	227	51	,	,	PUNCT
bracis-19081	227	52	a.	a.	NOUN
bracis-19081	227	53	:	:	PUNCT
bracis-19081	227	54	deep	deep	ADJ
bracis-19081	227	55	active	active	ADJ
bracis-19081	227	56	learning	learning	NOUN
bracis-19081	227	57	for	for	ADP
bracis-19081	227	58	named	name	VERB
bracis-19081	227	59	entity	entity	NOUN
bracis-19081	227	60	recognition	recognition	NOUN
bracis-19081	227	61	.	.	PUNCT
bracis-19081	228	1	in	in	ADP
bracis-19081	228	2	:	:	PUNCT
bracis-19081	228	3	proceedings	proceeding	NOUN
bracis-19081	228	4	of	of	ADP
bracis-19081	228	5	the	the	DET
bracis-19081	228	6	2nd	2nd	ADJ
bracis-19081	228	7	workshop	workshop	NOUN
bracis-19081	228	8	on	on	ADP
bracis-19081	228	9	representation	representation	NOUN
bracis-19081	228	10	learning	learning	NOUN
bracis-19081	228	11	for	for	ADP
bracis-19081	228	12	nlp	nlp	NOUN
bracis-19081	228	13	,	,	PUNCT
bracis-19081	228	14	pp	pp	ADJ
bracis-19081	228	15	.	.	PUNCT
bracis-19081	229	1	252–256	252–256	NUM
bracis-19081	229	2	.	.	PUNCT
bracis-19081	229	3	association	association	NOUN
bracis-19081	229	4	for	for	ADP
bracis-19081	229	5	computational	computational	ADJ
bracis-19081	229	6	linguistics	linguistic	NOUN
bracis-19081	229	7	,	,	PUNCT
bracis-19081	229	8	vancouver	vancouver	NOUN
bracis-19081	229	9	,	,	PUNCT
bracis-19081	229	10	august	august	PROPN
bracis-19081	229	11	2017	2017	NUM
bracis-19081	229	12	.	.	PUNCT
bracis-19081	230	1	https://doi.org/10.18653/v1/w17-2630	https://doi.org/10.18653/v1/w17-2630	PROPN
bracis-19081	230	2	siddhant	siddhant	NOUN
bracis-19081	230	3	,	,	PUNCT
bracis-19081	230	4	a.	a.	PROPN
bracis-19081	230	5	,	,	PUNCT
bracis-19081	230	6	lipton	lipton	PROPN
bracis-19081	230	7	,	,	PUNCT
bracis-19081	230	8	z.c	z.c	PROPN
bracis-19081	230	9	.	.	PROPN
bracis-19081	230	10	:	:	PUNCT
bracis-19081	231	1	deep	deep	ADJ
bracis-19081	231	2	bayesian	bayesian	NOUN
bracis-19081	231	3	active	active	ADJ
bracis-19081	231	4	learning	learning	NOUN
bracis-19081	231	5	for	for	ADP
bracis-19081	231	6	natural	natural	ADJ
bracis-19081	231	7	language	language	NOUN
bracis-19081	231	8	processing	processing	NOUN
bracis-19081	231	9	:	:	PUNCT
bracis-19081	231	10	results	result	NOUN
bracis-19081	231	11	of	of	ADP
bracis-19081	231	12	a	a	DET
bracis-19081	231	13	large	large	ADJ
bracis-19081	231	14	-	-	PUNCT
bracis-19081	231	15	scale	scale	NOUN
bracis-19081	231	16	empirical	empirical	ADJ
bracis-19081	231	17	study	study	NOUN
bracis-19081	231	18	.	.	PUNCT
bracis-19081	232	1	in	in	ADP
bracis-19081	232	2	:	:	PUNCT
bracis-19081	232	3	proceedings	proceeding	NOUN
bracis-19081	232	4	of	of	ADP
bracis-19081	232	5	the	the	DET
bracis-19081	232	6	2018	2018	NUM
bracis-19081	232	7	conference	conference	NOUN
bracis-19081	232	8	on	on	ADP
bracis-19081	232	9	empirical	empirical	ADJ
bracis-19081	232	10	methods	method	NOUN
bracis-19081	232	11	in	in	ADP
bracis-19081	232	12	natural	natural	ADJ
bracis-19081	232	13	language	language	NOUN
bracis-19081	232	14	processing	processing	NOUN
bracis-19081	232	15	,	,	PUNCT
bracis-19081	232	16	pp	pp	ADJ
bracis-19081	232	17	.	.	PUNCT
bracis-19081	232	18	2904–2909	2904–2909	NUM
bracis-19081	232	19	.	.	PUNCT
bracis-19081	233	1	association	association	NOUN
bracis-19081	233	2	for	for	ADP
bracis-19081	233	3	computational	computational	ADJ
bracis-19081	233	4	linguistics	linguistic	NOUN
bracis-19081	233	5	,	,	PUNCT
bracis-19081	233	6	brussels	brussels	PROPN
bracis-19081	233	7	,	,	PUNCT
bracis-19081	233	8	october	october	PROPN
bracis-19081	233	9	–	–	PUNCT
bracis-19081	233	10	november	november	PROPN
bracis-19081	233	11	2018	2018	NUM
bracis-19081	233	12	.	.	PUNCT
bracis-19081	234	1	https://doi.org/10.18653/v1/d18-1318	https://doi.org/10.18653/v1/d18-1318	PROPN
bracis-19081	234	2	tran	tran	PROPN
bracis-19081	234	3	,	,	PUNCT
bracis-19081	234	4	v.c	v.c	PROPN
bracis-19081	234	5	.	.	PROPN
bracis-19081	234	6	,	,	PUNCT
bracis-19081	234	7	nguyen	nguyen	PROPN
bracis-19081	234	8	,	,	PUNCT
bracis-19081	234	9	n.t	n.t	PROPN
bracis-19081	234	10	.	.	PROPN
bracis-19081	234	11	,	,	PUNCT
bracis-19081	234	12	fujita	fujita	PROPN
bracis-19081	234	13	,	,	PUNCT
bracis-19081	234	14	h.	h.	PROPN
bracis-19081	234	15	,	,	PUNCT
bracis-19081	234	16	hoang	hoang	PROPN
bracis-19081	234	17	,	,	PUNCT
bracis-19081	234	18	d.t	d.t	PROPN
bracis-19081	234	19	.	.	PROPN
bracis-19081	234	20	,	,	PUNCT
bracis-19081	234	21	hwang	hwang	PROPN
bracis-19081	234	22	,	,	PUNCT
bracis-19081	234	23	d.	d.	PROPN
bracis-19081	234	24	:	:	PUNCT
bracis-19081	234	25	a	a	DET
bracis-19081	234	26	combination	combination	NOUN
bracis-19081	234	27	of	of	ADP
bracis-19081	234	28	active	active	ADJ
bracis-19081	234	29	learning	learning	NOUN
bracis-19081	234	30	and	and	CCONJ
bracis-19081	234	31	self	self	NOUN
bracis-19081	234	32	-	-	PUNCT
bracis-19081	234	33	learning	learning	NOUN
bracis-19081	234	34	for	for	ADP
bracis-19081	234	35	named	name	VERB
bracis-19081	234	36	entity	entity	NOUN
bracis-19081	234	37	recognition	recognition	NOUN
bracis-19081	234	38	on	on	ADP
bracis-19081	234	39	twitter	twitter	NOUN
bracis-19081	234	40	using	use	VERB
bracis-19081	234	41	conditional	conditional	ADJ
bracis-19081	234	42	random	random	ADJ
bracis-19081	234	43	fields	field	NOUN
bracis-19081	234	44	.	.	PUNCT
bracis-19081	235	1	knowl.-based	knowl.-based	PROPN
bracis-19081	235	2	syst	syst	PROPN
bracis-19081	235	3	.	.	PUNCT
bracis-19081	236	1	132	132	NUM
bracis-19081	236	2	,	,	PUNCT
bracis-19081	236	3	179–187	179–187	NUM
bracis-19081	236	4	(	(	PUNCT
bracis-19081	236	5	2017	2017	NUM
bracis-19081	236	6	)	)	PUNCT
bracis-19081	236	7	.	.	PUNCT
bracis-19081	237	1	https://doi.org/10.1016/j.knosys.2017.06.023	https://doi.org/10.1016/j.knosys.2017.06.023	PROPN
bracis-19081	237	2	article	article	NOUN
bracis-19081	237	3	  	  	SPACE
bracis-19081	237	4	google	google	PROPN
bracis-19081	237	5	scholar	scholar	NOUN
bracis-19081	237	6	  	  	SPACE
bracis-19081	237	7	zhu	zhu	PROPN
bracis-19081	237	8	,	,	PUNCT
bracis-19081	237	9	j.	j.	PROPN
bracis-19081	237	10	,	,	PUNCT
bracis-19081	237	11	wang	wang	PROPN
bracis-19081	237	12	,	,	PUNCT
bracis-19081	237	13	h.	h.	PROPN
bracis-19081	237	14	,	,	PUNCT
bracis-19081	237	15	hovy	hovy	PROPN
bracis-19081	237	16	,	,	PUNCT
bracis-19081	237	17	e.	e.	PROPN
bracis-19081	237	18	,	,	PUNCT
bracis-19081	237	19	ma	ma	PROPN
bracis-19081	237	20	,	,	PUNCT
bracis-19081	237	21	m.	m.	NOUN
bracis-19081	237	22	:	:	PUNCT
bracis-19081	237	23	confidence	confidence	NOUN
bracis-19081	237	24	-	-	PUNCT
bracis-19081	237	25	based	base	VERB
bracis-19081	237	26	stopping	stopping	NOUN
bracis-19081	237	27	criteria	criterion	NOUN
bracis-19081	237	28	for	for	ADP
bracis-19081	237	29	active	active	ADJ
bracis-19081	237	30	learning	learning	NOUN
bracis-19081	237	31	for	for	ADP
bracis-19081	237	32	data	datum	NOUN
bracis-19081	237	33	annotation	annotation	NOUN
bracis-19081	237	34	.	.	PUNCT
bracis-19081	238	1	acm	acm	PROPN
bracis-19081	238	2	trans	trans	PROPN
bracis-19081	238	3	.	.	PROPN
bracis-19081	238	4	speech	speech	PROPN
bracis-19081	238	5	lang	lang	PROPN
bracis-19081	238	6	.	.	PUNCT
bracis-19081	238	7	process	process	NOUN
bracis-19081	238	8	.	.	PUNCT
bracis-19081	239	1	6(3	6(3	NUM
bracis-19081	239	2	)	)	PUNCT
bracis-19081	239	3	,	,	PUNCT
bracis-19081	239	4	april	april	PROPN
bracis-19081	239	5	2010	2010	NUM
bracis-19081	239	6	.	.	PUNCT
bracis-19081	240	1	https://doi.org/10.1145/1753783.1753784	https://doi.org/10.1145/1753783.1753784	PROPN
bracis-19081	240	2	download	download	NOUN
bracis-19081	240	3	references	reference	NOUN
bracis-19081	240	4	acknowledgements	acknowledgement	NOUN
bracis-19081	240	5	the	the	DET
bracis-19081	240	6	authors	author	NOUN
bracis-19081	240	7	are	be	AUX
bracis-19081	240	8	supported	support	VERB
bracis-19081	240	9	by	by	ADP
bracis-19081	240	10	the	the	DET
bracis-19081	240	11	fundação	fundação	NOUN
bracis-19081	240	12	de	de	PROPN
bracis-19081	240	13	apoio	apoio	NOUN
bracis-19081	240	14	a	a	DET
bracis-19081	240	15	pesquisa	pesquisa	NOUN
bracis-19081	240	16	do	do	AUX
bracis-19081	240	17	distritio	distritio	VERB
bracis-19081	240	18	federal	federal	ADJ
bracis-19081	240	19	(	(	PUNCT
bracis-19081	240	20	fap	fap	NOUN
bracis-19081	240	21	-	-	PUNCT
bracis-19081	240	22	df	df	NOUN
bracis-19081	240	23	)	)	PUNCT
bracis-19081	240	24	as	as	ADP
bracis-19081	240	25	members	member	NOUN
bracis-19081	240	26	of	of	ADP
bracis-19081	240	27	the	the	DET
bracis-19081	240	28	knowledge	knowledge	NOUN
bracis-19081	240	29	extraction	extraction	NOUN
bracis-19081	240	30	from	from	ADP
bracis-19081	240	31	documents	document	NOUN
bracis-19081	240	32	of	of	ADP
bracis-19081	240	33	legal	legal	ADJ
bracis-19081	240	34	content	content	NOUN
bracis-19081	240	35	(	(	PUNCT
bracis-19081	240	36	knedle	knedle	NOUN
bracis-19081	240	37	)	)	PUNCT
bracis-19081	240	38	project	project	NOUN
bracis-19081	240	39	from	from	ADP
bracis-19081	240	40	the	the	DET
bracis-19081	240	41	university	university	PROPN
bracis-19081	240	42	of	of	ADP
bracis-19081	240	43	brasilia	brasilia	PROPN
bracis-19081	240	44	.	.	PUNCT
bracis-19081	241	1	author	author	NOUN
bracis-19081	241	2	information	information	NOUN
bracis-19081	241	3	authors	author	NOUN
bracis-19081	241	4	and	and	CCONJ
bracis-19081	241	5	affiliations	affiliation	NOUN
bracis-19081	241	6	university	university	PROPN
bracis-19081	241	7	of	of	ADP
bracis-19081	241	8	brasilia	brasilia	PROPN
bracis-19081	241	9	,	,	PUNCT
bracis-19081	241	10	brasilia	brasilia	PROPN
bracis-19081	241	11	,	,	PUNCT
bracis-19081	241	12	df	df	PROPN
bracis-19081	241	13	,	,	PUNCT
bracis-19081	241	14	brazil	brazil	PROPN
bracis-19081	241	15	josé	josé	PROPN
bracis-19081	241	16	reinaldo	reinaldo	PROPN
bracis-19081	241	17	c.	c.	PROPN
bracis-19081	241	18	s.	s.	PROPN
bracis-19081	241	19	a.	a.	PROPN
bracis-19081	242	1	v.	v.	PROPN
bracis-19081	242	2	s.	s.	PROPN
bracis-19081	242	3	neto	neto	PROPN
bracis-19081	242	4	 	 	SPACE
bracis-19081	242	5	&	&	CCONJ
bracis-19081	242	6	 	 	SPACE
bracis-19081	242	7	thiago	thiago	PROPN
bracis-19081	242	8	de	de	PROPN
bracis-19081	242	9	paulo	paulo	PROPN
bracis-19081	242	10	faleiros	faleiros	PROPN
bracis-19081	242	11	authors	author	NOUN
bracis-19081	242	12	josé	josé	PROPN
bracis-19081	242	13	reinaldo	reinaldo	PROPN
bracis-19081	242	14	c.	c.	PROPN
bracis-19081	242	15	s.	s.	PROPN
bracis-19081	242	16	a.	a.	PROPN
bracis-19081	243	1	v.	v.	PROPN
bracis-19081	243	2	s.	s.	PROPN
bracis-19081	243	3	netoview	netoview	PROPN
bracis-19081	243	4	author	author	NOUN
bracis-19081	243	5	publications	publication	NOUN
bracis-19081	243	6	search	search	NOUN
bracis-19081	243	7	author	author	NOUN
bracis-19081	243	8	on	on	ADP
bracis-19081	243	9	:	:	PUNCT
bracis-19081	243	10	pubmed	pubmed	PROPN
bracis-19081	243	11	 	 	SPACE
bracis-19081	243	12	google	google	PROPN
bracis-19081	243	13	scholar	scholar	NOUN
bracis-19081	243	14	thiago	thiago	PROPN
bracis-19081	243	15	de	de	PROPN
bracis-19081	243	16	paulo	paulo	PROPN
bracis-19081	243	17	faleirosview	faleirosview	PROPN
bracis-19081	243	18	author	author	NOUN
bracis-19081	243	19	publications	publication	NOUN
bracis-19081	243	20	search	search	NOUN
bracis-19081	243	21	author	author	NOUN
bracis-19081	243	22	on	on	ADP
bracis-19081	243	23	:	:	PUNCT
bracis-19081	243	24	pubmed	pubmed	PROPN
bracis-19081	243	25	 	 	SPACE
bracis-19081	243	26	google	google	PROPN
bracis-19081	243	27	scholar	scholar	NOUN
bracis-19081	243	28	editor	editor	NOUN
bracis-19081	243	29	information	information	NOUN
bracis-19081	243	30	editors	editor	NOUN
bracis-19081	243	31	and	and	CCONJ
bracis-19081	243	32	affiliations	affiliation	NOUN
bracis-19081	243	33	universidade	universidade	PROPN
bracis-19081	243	34	federal	federal	PROPN
bracis-19081	243	35	de	de	X
bracis-19081	243	36	sergipe	sergipe	PROPN
bracis-19081	243	37	,	,	PUNCT
bracis-19081	243	38	são	são	NOUN
bracis-19081	243	39	cristóvão	cristóvão	PROPN
bracis-19081	243	40	,	,	PUNCT
bracis-19081	243	41	brazil	brazil	PROPN
bracis-19081	243	42	andré	andré	PROPN
bracis-19081	243	43	britto	britto	PROPN
bracis-19081	243	44	universidade	universidade	PROPN
bracis-19081	243	45	de	de	PROPN
bracis-19081	243	46	são	são	PROPN
bracis-19081	243	47	paulo	paulo	PROPN
bracis-19081	243	48	,	,	PUNCT
bracis-19081	243	49	são	são	PROPN
bracis-19081	243	50	paulo	paulo	PROPN
bracis-19081	243	51	,	,	PUNCT
bracis-19081	243	52	brazil	brazil	PROPN
bracis-19081	243	53	karina	karina	PROPN
bracis-19081	243	54	valdivia	valdivia	PROPN
bracis-19081	243	55	delgado	delgado	VERB
bracis-19081	243	56	rights	right	NOUN
bracis-19081	243	57	and	and	CCONJ
bracis-19081	243	58	permissions	permission	NOUN
bracis-19081	243	59	reprints	reprint	NOUN
bracis-19081	243	60	and	and	CCONJ
bracis-19081	243	61	permissions	permission	VERB
bracis-19081	243	62	copyright	copyright	NOUN
bracis-19081	243	63	information	information	NOUN
bracis-19081	243	64	©	©	PROPN
bracis-19081	243	65	2021	2021	NUM
bracis-19081	243	66	springer	springer	NOUN
bracis-19081	243	67	nature	nature	NOUN
bracis-19081	243	68	switzerland	switzerland	PROPN
bracis-19081	243	69	ag	ag	PROPN
bracis-19081	243	70	about	about	ADP
bracis-19081	243	71	this	this	DET
bracis-19081	243	72	paper	paper	NOUN
bracis-19081	243	73	cite	cite	VERB
bracis-19081	243	74	this	this	DET
bracis-19081	243	75	paper	paper	NOUN
bracis-19081	243	76	neto	neto	NOUN
bracis-19081	243	77	,	,	PUNCT
bracis-19081	243	78	j.r.c.s.a.v.s	j.r.c.s.a.v.s	PROPN
bracis-19081	243	79	.	.	PROPN
bracis-19081	243	80	,	,	PUNCT
bracis-19081	243	81	faleiros	faleiros	PROPN
bracis-19081	243	82	,	,	PUNCT
bracis-19081	243	83	t.d.p	t.d.p	X
bracis-19081	243	84	.	.	PUNCT
bracis-19081	244	1	(	(	PUNCT
bracis-19081	244	2	2021	2021	NUM
bracis-19081	244	3	)	)	PUNCT
bracis-19081	244	4	.	.	PUNCT
bracis-19081	245	1	deep	deep	ADJ
bracis-19081	245	2	active	active	ADJ
bracis-19081	245	3	-	-	PUNCT
bracis-19081	245	4	self	self	NOUN
bracis-19081	245	5	learning	learning	NOUN
bracis-19081	245	6	applied	apply	VERB
bracis-19081	245	7	to	to	ADP
bracis-19081	245	8	named	name	VERB
bracis-19081	245	9	entity	entity	NOUN
bracis-19081	245	10	recognition	recognition	NOUN
bracis-19081	245	11	.	.	PUNCT
bracis-19081	246	1	in	in	ADP
bracis-19081	246	2	:	:	PUNCT
bracis-19081	246	3	britto	britto	PROPN
bracis-19081	246	4	,	,	PUNCT
bracis-19081	246	5	a.	a.	PROPN
bracis-19081	246	6	,	,	PUNCT
bracis-19081	246	7	valdivia	valdivia	PROPN
bracis-19081	246	8	delgado	delgado	PROPN
bracis-19081	246	9	,	,	PUNCT
bracis-19081	246	10	k.	k.	PROPN
bracis-19081	246	11	(	(	PUNCT
bracis-19081	246	12	eds	eds	PROPN
bracis-19081	246	13	)	)	PUNCT
bracis-19081	246	14	intelligent	intelligent	ADJ
bracis-19081	246	15	systems	system	NOUN
bracis-19081	246	16	.	.	PUNCT
bracis-19081	247	1	bracis	bracis	PROPN
bracis-19081	247	2	2021	2021	NUM
bracis-19081	247	3	.	.	PUNCT
bracis-19081	248	1	lecture	lecture	NOUN
bracis-19081	248	2	notes	note	NOUN
bracis-19081	248	3	in	in	ADP
bracis-19081	248	4	computer	computer	NOUN
bracis-19081	248	5	science	science	NOUN
bracis-19081	248	6	(	(	PUNCT
bracis-19081	248	7	)	)	PUNCT
bracis-19081	248	8	,	,	PUNCT
bracis-19081	248	9	vol	vol	NOUN
bracis-19081	248	10	13074	13074	NUM
bracis-19081	248	11	.	.	PUNCT
bracis-19081	249	1	springer	springer	NOUN
bracis-19081	249	2	,	,	PUNCT
bracis-19081	249	3	cham	cham	PROPN
bracis-19081	249	4	.	.	PUNCT
bracis-19081	250	1	https://doi.org/10.1007/978-3-030-91699-2_28	https://doi.org/10.1007/978-3-030-91699-2_28	NOUN
bracis-19081	250	2	download	download	NOUN
bracis-19081	250	3	citation	citation	NOUN
bracis-19081	250	4	.ris	.ris	PUNCT
bracis-19081	250	5	.enw	.enw	PROPN
bracis-19081	250	6	.bib	.bib	PUNCT
bracis-19081	251	1	doi	doi	PROPN
bracis-19081	251	2	:	:	PUNCT
bracis-19081	251	3	https://doi.org/10.1007/978-3-030-91699-2_28	https://doi.org/10.1007/978-3-030-91699-2_28	NOUN
bracis-19081	251	4	published	publish	VERB
bracis-19081	251	5	:	:	PUNCT
bracis-19081	251	6	28	28	NUM
bracis-19081	251	7	november	november	PROPN
bracis-19081	251	8	2021	2021	NUM
bracis-19081	251	9	publisher	publisher	NOUN
bracis-19081	251	10	name	name	NOUN
bracis-19081	251	11	:	:	PUNCT
bracis-19081	251	12	springer	springer	NOUN
bracis-19081	251	13	,	,	PUNCT
bracis-19081	251	14	cham	cham	PROPN
bracis-19081	251	15	print	print	PROPN
bracis-19081	251	16	isbn	isbn	PROPN
bracis-19081	251	17	:	:	PUNCT
bracis-19081	251	18	978	978	NUM
bracis-19081	251	19	-	-	SYM
bracis-19081	251	20	3	3	NUM
bracis-19081	251	21	-	-	PUNCT
bracis-19081	251	22	030	030	NUM
bracis-19081	251	23	-	-	PUNCT
bracis-19081	251	24	91698	91698	NUM
bracis-19081	251	25	-	-	SYM
bracis-19081	251	26	5	5	NUM
bracis-19081	251	27	online	online	ADJ
bracis-19081	251	28	isbn	isbn	NOUN
bracis-19081	251	29	:	:	PUNCT
bracis-19081	251	30	978	978	NUM
bracis-19081	251	31	-	-	SYM
bracis-19081	251	32	3	3	NUM
bracis-19081	251	33	-	-	PUNCT
bracis-19081	251	34	030	030	NUM
bracis-19081	251	35	-	-	PUNCT
bracis-19081	251	36	91699	91699	NUM
bracis-19081	251	37	-	-	SYM
bracis-19081	251	38	2	2	NUM
bracis-19081	251	39	ebook	ebook	NOUN
bracis-19081	251	40	packages	package	NOUN
bracis-19081	251	41	:	:	PUNCT
bracis-19081	251	42	computer	computer	NOUN
bracis-19081	251	43	sciencecomputer	sciencecomputer	NOUN
bracis-19081	251	44	science	science	NOUN
bracis-19081	251	45	(	(	PUNCT
bracis-19081	251	46	r0	r0	NOUN
bracis-19081	251	47	)	)	PUNCT
bracis-19081	251	48	share	share	VERB
bracis-19081	251	49	this	this	DET
bracis-19081	251	50	paper	paper	NOUN
bracis-19081	251	51	anyone	anyone	PRON
bracis-19081	251	52	you	you	PRON
bracis-19081	251	53	share	share	VERB
bracis-19081	251	54	the	the	DET
bracis-19081	251	55	following	follow	VERB
bracis-19081	251	56	link	link	NOUN
bracis-19081	251	57	with	with	ADP
bracis-19081	251	58	will	will	AUX
bracis-19081	251	59	be	be	AUX
bracis-19081	251	60	able	able	ADJ
bracis-19081	251	61	to	to	PART
bracis-19081	251	62	read	read	VERB
bracis-19081	251	63	this	this	DET
bracis-19081	251	64	content	content	NOUN
bracis-19081	251	65	:	:	PUNCT
bracis-19081	251	66	get	get	VERB
bracis-19081	251	67	shareable	shareable	ADJ
bracis-19081	251	68	linksorry	linksorry	NOUN
bracis-19081	251	69	,	,	PUNCT
bracis-19081	251	70	a	a	DET
bracis-19081	251	71	shareable	shareable	ADJ
bracis-19081	251	72	link	link	NOUN
bracis-19081	251	73	is	be	AUX
bracis-19081	251	74	not	not	PART
bracis-19081	251	75	currently	currently	ADV
bracis-19081	251	76	available	available	ADJ
bracis-19081	251	77	for	for	ADP
bracis-19081	251	78	this	this	DET
bracis-19081	251	79	article	article	NOUN
bracis-19081	251	80	.	.	PUNCT
bracis-19081	252	1	copy	copy	VERB
bracis-19081	252	2	shareable	shareable	ADJ
bracis-19081	252	3	link	link	NOUN
bracis-19081	252	4	to	to	PART
bracis-19081	252	5	clipboard	clipboard	NOUN
bracis-19081	252	6	provided	provide	VERB
bracis-19081	252	7	by	by	ADP
bracis-19081	252	8	the	the	DET
bracis-19081	252	9	springer	springer	NOUN
bracis-19081	252	10	nature	nature	PROPN
bracis-19081	252	11	sharedit	sharedit	PROPN
bracis-19081	252	12	content	content	NOUN
bracis-19081	252	13	-	-	PUNCT
bracis-19081	252	14	sharing	share	VERB
bracis-19081	252	15	initiative	initiative	NOUN
bracis-19081	252	16	keywords	keyword	NOUN
bracis-19081	252	17	deep	deep	ADJ
bracis-19081	252	18	active	active	ADJ
bracis-19081	252	19	learning	learn	VERB
bracis-19081	252	20	self	self	NOUN
bracis-19081	252	21	learning	learning	NOUN
bracis-19081	252	22	named	name	VERB
bracis-19081	252	23	entity	entity	NOUN
bracis-19081	252	24	recognition	recognition	NOUN
bracis-19081	253	1	deep	deep	ADJ
bracis-19081	253	2	learning	learning	NOUN
bracis-19081	253	3	publish	publish	VERB
bracis-19081	253	4	with	with	ADP
bracis-19081	253	5	us	us	PROPN
bracis-19081	253	6	policies	policy	NOUN
bracis-19081	253	7	and	and	CCONJ
bracis-19081	253	8	ethics	ethic	NOUN
bracis-19081	253	9	profiles	profile	NOUN
bracis-19081	253	10	thiago	thiago	PROPN
bracis-19081	253	11	de	de	PROPN
bracis-19081	253	12	paulo	paulo	PROPN
bracis-19081	253	13	faleiros	faleiros	PROPN
bracis-19081	253	14	view	view	NOUN
bracis-19081	253	15	author	author	NOUN
bracis-19081	253	16	profile	profile	NOUN
bracis-19081	253	17	search	search	NOUN
bracis-19081	253	18	search	search	NOUN
bracis-19081	253	19	by	by	ADP
bracis-19081	253	20	keyword	keyword	NOUN
bracis-19081	253	21	or	or	CCONJ
bracis-19081	253	22	author	author	NOUN
bracis-19081	253	23	search	search	NOUN
bracis-19081	253	24	navigation	navigation	NOUN
bracis-19081	253	25	find	find	VERB
bracis-19081	253	26	a	a	DET
bracis-19081	253	27	journal	journal	NOUN
bracis-19081	253	28	publish	publish	VERB
bracis-19081	253	29	with	with	ADP
bracis-19081	253	30	us	we	PRON
bracis-19081	253	31	track	track	VERB
bracis-19081	253	32	your	your	PRON
bracis-19081	253	33	research	research	NOUN
bracis-19081	253	34	discover	discover	VERB
bracis-19081	253	35	content	content	NOUN
bracis-19081	253	36	journals	journal	NOUN
bracis-19081	253	37	a	a	DET
bracis-19081	253	38	-	-	PUNCT
bracis-19081	253	39	z	z	NOUN
bracis-19081	253	40	books	book	NOUN
bracis-19081	253	41	a	a	DET
bracis-19081	253	42	-	-	PUNCT
bracis-19081	253	43	z	z	NOUN
bracis-19081	253	44	publish	publish	NOUN
bracis-19081	253	45	with	with	ADP
bracis-19081	253	46	us	us	PROPN
bracis-19081	253	47	journal	journal	PROPN
bracis-19081	253	48	finder	finder	PROPN
bracis-19081	253	49	publish	publish	VERB
bracis-19081	253	50	your	your	PRON
bracis-19081	253	51	research	research	NOUN
bracis-19081	253	52	language	language	NOUN
bracis-19081	253	53	editing	edit	VERB
bracis-19081	253	54	open	open	ADJ
bracis-19081	253	55	access	access	NOUN
bracis-19081	253	56	publishing	publishing	NOUN
bracis-19081	253	57	products	product	NOUN
bracis-19081	253	58	and	and	CCONJ
bracis-19081	253	59	services	service	NOUN
bracis-19081	253	60	our	our	PRON
bracis-19081	253	61	products	product	NOUN
bracis-19081	253	62	librarians	librarian	VERB
bracis-19081	253	63	societies	society	NOUN
bracis-19081	253	64	partners	partner	NOUN
bracis-19081	253	65	and	and	CCONJ
bracis-19081	253	66	advertisers	advertiser	NOUN
bracis-19081	253	67	our	our	PRON
bracis-19081	253	68	brands	brand	NOUN
bracis-19081	253	69	springer	springer	NOUN
bracis-19081	253	70	nature	nature	PROPN
bracis-19081	253	71	portfolio	portfolio	PROPN
bracis-19081	253	72	bmc	bmc	PROPN
bracis-19081	253	73	palgrave	palgrave	PROPN
bracis-19081	253	74	macmillan	macmillan	PROPN
bracis-19081	253	75	apress	apress	PROPN
bracis-19081	253	76	discover	discover	VERB
bracis-19081	253	77	your	your	PRON
bracis-19081	253	78	privacy	privacy	NOUN
bracis-19081	253	79	choices	choice	NOUN
bracis-19081	253	80	/	/	SYM
bracis-19081	253	81	manage	manage	NOUN
bracis-19081	253	82	cookies	cookie	NOUN
bracis-19081	253	83	your	your	PRON
bracis-19081	253	84	us	us	PROPN
bracis-19081	254	1	state	state	NOUN
bracis-19081	254	2	privacy	privacy	NOUN
bracis-19081	254	3	rights	right	NOUN
bracis-19081	254	4	accessibility	accessibility	NOUN
bracis-19081	254	5	statement	statement	NOUN
bracis-19081	254	6	terms	term	NOUN
bracis-19081	254	7	and	and	CCONJ
bracis-19081	254	8	conditions	condition	NOUN
bracis-19081	254	9	privacy	privacy	NOUN
bracis-19081	254	10	policy	policy	NOUN
bracis-19081	254	11	help	help	NOUN
bracis-19081	254	12	and	and	CCONJ
bracis-19081	254	13	support	support	VERB
bracis-19081	254	14	legal	legal	ADJ
bracis-19081	254	15	notice	notice	NOUN
bracis-19081	254	16	cancel	cancel	VERB
bracis-19081	254	17	contracts	contract	NOUN
bracis-19081	254	18	here	here	ADV
bracis-19081	254	19	129.74.145.123	129.74.145.123	NUM
bracis-19081	254	20	hesburgh	hesburgh	PROPN
bracis-19081	254	21	library	library	PROPN
bracis-19081	254	22	er	er	INTJ
bracis-19081	254	23	unit	unit	NOUN
bracis-19081	254	24	(	(	PUNCT
bracis-19081	254	25	3005732405	3005732405	NUM
bracis-19081	254	26	)	)	PUNCT
bracis-19081	254	27	northeast	northeast	ADJ
bracis-19081	254	28	research	research	NOUN
bracis-19081	254	29	libraries	library	NOUN
bracis-19081	254	30	(	(	PUNCT
bracis-19081	254	31	nerl	nerl	PROPN
bracis-19081	254	32	)	)	PUNCT
bracis-19081	254	33	(	(	PUNCT
bracis-19081	254	34	8200828607	8200828607	NUM
bracis-19081	254	35	)	)	PUNCT
bracis-19081	254	36	nerl	nerl	VERB
bracis-19081	254	37	ta	ta	X
bracis-19081	254	38	account	account	NOUN
bracis-19081	254	39	(	(	PUNCT
bracis-19081	254	40	3006206169	3006206169	NUM
bracis-19081	254	41	)	)	PUNCT
bracis-19081	254	42	university	university	NOUN
bracis-19081	254	43	of	of	ADP
bracis-19081	254	44	notre	notre	PROPN
bracis-19081	254	45	dame	dame	PROPN
bracis-19081	254	46	hesburgh	hesburgh	PROPN
bracis-19081	254	47	library	library	NOUN
bracis-19081	254	48	(	(	PUNCT
bracis-19081	254	49	3000184373	3000184373	NUM
bracis-19081	254	50	)	)	PUNCT
bracis-19081	255	1	©	©	ADP
bracis-19081	255	2	2025	2025	NUM
bracis-19081	255	3	springer	springer	NOUN
bracis-19081	255	4	nature	nature	NOUN