id	sid	tid	token	lemma	pos
fcis-7982	1	1	frontiers	frontier	NOUN
fcis-7982	1	2	in	in	ADP
fcis-7982	1	3	computing	computing	NOUN
fcis-7982	1	4	and	and	CCONJ
fcis-7982	1	5	intelligent	intelligent	ADJ
fcis-7982	1	6	systems	system	NOUN
fcis-7982	1	7	issn	issn	VERB
fcis-7982	1	8	:	:	PUNCT
fcis-7982	1	9	2832	2832	NUM
fcis-7982	1	10	-	-	SYM
fcis-7982	1	11	6024	6024	NUM
fcis-7982	1	12	|	|	NOUN
fcis-7982	1	13	vol	vol	NOUN
fcis-7982	1	14	.	.	PROPN
fcis-7982	2	1	3	3	NUM
fcis-7982	2	2	,	,	PUNCT
fcis-7982	2	3	no	no	INTJ
fcis-7982	2	4	.	.	NOUN
fcis-7982	2	5	3	3	NUM
fcis-7982	2	6	,	,	PUNCT
fcis-7982	2	7	2023	2023	NUM
fcis-7982	2	8	1	1	NUM
fcis-7982	2	9	one	one	NUM
fcis-7982	2	10	-	-	PUNCT
fcis-7982	2	11	shot	shot	NOUN
fcis-7982	2	12	based	base	VERB
fcis-7982	2	13	knowledge	knowledge	NOUN
fcis-7982	2	14	graph	graph	NOUN
fcis-7982	2	15	embedded	embed	VERB
fcis-7982	2	16	neural	neural	ADJ
fcis-7982	2	17	architecture	architecture	NOUN
fcis-7982	2	18	search	search	NOUN
fcis-7982	2	19	algorithm	algorithm	NOUN
fcis-7982	2	20	wenli	wenli	PROPN
fcis-7982	2	21	li	li	PROPN
fcis-7982	2	22	,	,	PUNCT
fcis-7982	2	23	gang	gang	PROPN
fcis-7982	2	24	wu	wu	PROPN
fcis-7982	2	25	*	*	PROPN
fcis-7982	2	26	school	school	NOUN
fcis-7982	2	27	of	of	ADP
fcis-7982	2	28	computer	computer	NOUN
fcis-7982	2	29	and	and	CCONJ
fcis-7982	2	30	engineering	engineering	NOUN
fcis-7982	2	31	,	,	PUNCT
fcis-7982	2	32	northeastern	northeastern	ADJ
fcis-7982	2	33	university	university	PROPN
fcis-7982	2	34	,	,	PUNCT
fcis-7982	2	35	shenyang	shenyang	PROPN
fcis-7982	2	36	110819	110819	NUM
fcis-7982	2	37	,	,	PUNCT
fcis-7982	2	38	china	china	PROPN
fcis-7982	2	39	*	*	PUNCT
fcis-7982	2	40	corresponding	correspond	VERB
fcis-7982	2	41	author	author	NOUN
fcis-7982	2	42	:	:	PUNCT
fcis-7982	2	43	gang	gang	PROPN
fcis-7982	2	44	wu	wu	PROPN
fcis-7982	2	45	(	(	PUNCT
fcis-7982	2	46	email	email	NOUN
fcis-7982	2	47	:	:	PUNCT
fcis-7982	2	48	wugang@mail.neu.edu.cn	wugang@mail.neu.edu.cn	NOUN
fcis-7982	2	49	)	)	PUNCT
fcis-7982	2	50	abstract	abstract	NOUN
fcis-7982	2	51	:	:	PUNCT
fcis-7982	2	52	the	the	DET
fcis-7982	2	53	quality	quality	NOUN
fcis-7982	2	54	of	of	ADP
fcis-7982	2	55	embeddings	embedding	NOUN
fcis-7982	2	56	is	be	AUX
fcis-7982	2	57	crucial	crucial	ADJ
fcis-7982	2	58	for	for	ADP
fcis-7982	2	59	downstream	downstream	ADJ
fcis-7982	2	60	tasks	task	NOUN
fcis-7982	2	61	in	in	ADP
fcis-7982	2	62	knowledge	knowledge	NOUN
fcis-7982	2	63	graphs	graph	NOUN
fcis-7982	2	64	.	.	PUNCT
fcis-7982	3	1	researchers	researcher	NOUN
fcis-7982	3	2	usually	usually	ADV
fcis-7982	3	3	introduce	introduce	VERB
fcis-7982	3	4	neural	neural	ADJ
fcis-7982	3	5	network	network	NOUN
fcis-7982	3	6	architecture	architecture	NOUN
fcis-7982	3	7	search	search	NOUN
fcis-7982	3	8	into	into	ADP
fcis-7982	3	9	knowledge	knowledge	NOUN
fcis-7982	3	10	graph	graph	NOUN
fcis-7982	3	11	embedding	embed	VERB
fcis-7982	3	12	for	for	ADP
fcis-7982	3	13	machine	machine	NOUN
fcis-7982	3	14	automatic	automatic	ADJ
fcis-7982	3	15	construction	construction	NOUN
fcis-7982	3	16	of	of	ADP
fcis-7982	3	17	appropriate	appropriate	ADJ
fcis-7982	3	18	neural	neural	ADJ
fcis-7982	3	19	networks	network	NOUN
fcis-7982	3	20	for	for	ADP
fcis-7982	3	21	each	each	DET
fcis-7982	3	22	dataset	dataset	NOUN
fcis-7982	3	23	.	.	PUNCT
fcis-7982	4	1	an	an	DET
fcis-7982	4	2	existing	exist	VERB
fcis-7982	4	3	approach	approach	NOUN
fcis-7982	4	4	is	be	AUX
fcis-7982	4	5	to	to	PART
fcis-7982	4	6	divide	divide	VERB
fcis-7982	4	7	the	the	DET
fcis-7982	4	8	search	search	NOUN
fcis-7982	4	9	space	space	NOUN
fcis-7982	4	10	into	into	ADP
fcis-7982	4	11	macro	macro	ADJ
fcis-7982	4	12	search	search	NOUN
fcis-7982	4	13	space	space	NOUN
fcis-7982	4	14	and	and	CCONJ
fcis-7982	4	15	micro	micro	ADJ
fcis-7982	4	16	search	search	NOUN
fcis-7982	4	17	space	space	NOUN
fcis-7982	4	18	.	.	PUNCT
fcis-7982	5	1	the	the	DET
fcis-7982	5	2	search	search	NOUN
fcis-7982	5	3	strategy	strategy	NOUN
fcis-7982	5	4	for	for	ADP
fcis-7982	5	5	micro	micro	ADJ
fcis-7982	5	6	space	space	NOUN
fcis-7982	5	7	is	be	AUX
fcis-7982	5	8	based	base	VERB
fcis-7982	5	9	on	on	ADP
fcis-7982	5	10	one	one	NUM
fcis-7982	5	11	-	-	PUNCT
fcis-7982	5	12	shot	shot	NOUN
fcis-7982	5	13	weight	weight	NOUN
fcis-7982	5	14	sharing	sharing	NOUN
fcis-7982	5	15	strategy	strategy	NOUN
fcis-7982	5	16	,	,	PUNCT
fcis-7982	5	17	but	but	CCONJ
fcis-7982	5	18	it	it	PRON
fcis-7982	5	19	will	will	AUX
fcis-7982	5	20	lead	lead	VERB
fcis-7982	5	21	to	to	ADP
fcis-7982	5	22	all	all	DET
fcis-7982	5	23	the	the	DET
fcis-7982	5	24	information	information	NOUN
fcis-7982	5	25	obtained	obtain	VERB
fcis-7982	5	26	from	from	ADP
fcis-7982	5	27	the	the	DET
fcis-7982	5	28	previous	previous	ADJ
fcis-7982	5	29	supernet	supernet	NOUN
fcis-7982	5	30	training	training	NOUN
fcis-7982	5	31	is	be	AUX
fcis-7982	5	32	discarded	discard	VERB
fcis-7982	5	33	and	and	CCONJ
fcis-7982	5	34	the	the	DET
fcis-7982	5	35	advantages	advantage	NOUN
fcis-7982	5	36	of	of	ADP
fcis-7982	5	37	one	one	NUM
fcis-7982	5	38	-	-	PUNCT
fcis-7982	5	39	shot	shot	NOUN
fcis-7982	5	40	algorithm	algorithm	NOUN
fcis-7982	5	41	are	be	AUX
fcis-7982	5	42	not	not	PART
fcis-7982	5	43	fully	fully	ADV
fcis-7982	5	44	utilized	utilize	VERB
fcis-7982	5	45	.	.	PUNCT
fcis-7982	6	1	in	in	ADP
fcis-7982	6	2	this	this	DET
fcis-7982	6	3	paper	paper	NOUN
fcis-7982	6	4	,	,	PUNCT
fcis-7982	6	5	we	we	PRON
fcis-7982	6	6	conduct	conduct	VERB
fcis-7982	6	7	experiments	experiment	NOUN
fcis-7982	6	8	on	on	ADP
fcis-7982	6	9	common	common	ADJ
fcis-7982	6	10	datasets	dataset	NOUN
fcis-7982	6	11	for	for	ADP
fcis-7982	6	12	two	two	NUM
fcis-7982	6	13	important	important	ADJ
fcis-7982	6	14	downstream	downstream	ADJ
fcis-7982	6	15	tasks	task	NOUN
fcis-7982	6	16	of	of	ADP
fcis-7982	6	17	knowledge	knowledge	NOUN
fcis-7982	6	18	graph	graph	NOUN
fcis-7982	6	19	embedding	embed	VERB
fcis-7982	6	20	entity	entity	NOUN
fcis-7982	6	21	alignment	alignment	NOUN
fcis-7982	6	22	and	and	CCONJ
fcis-7982	6	23	link	link	VERB
fcis-7982	6	24	prediction	prediction	NOUN
fcis-7982	6	25	problems	problem	NOUN
fcis-7982	6	26	,	,	PUNCT
fcis-7982	6	27	respectively	respectively	ADV
fcis-7982	6	28	-	-	PUNCT
fcis-7982	6	29	and	and	CCONJ
fcis-7982	6	30	compare	compare	VERB
fcis-7982	6	31	the	the	DET
fcis-7982	6	32	search	search	NOUN
fcis-7982	6	33	performance	performance	NOUN
fcis-7982	6	34	with	with	ADP
fcis-7982	6	35	existing	exist	VERB
fcis-7982	6	36	manually	manually	ADV
fcis-7982	6	37	designed	design	VERB
fcis-7982	6	38	neural	neural	ADJ
fcis-7982	6	39	networks	network	NOUN
fcis-7982	6	40	as	as	ADV
fcis-7982	6	41	well	well	ADV
fcis-7982	6	42	as	as	ADP
fcis-7982	6	43	good	good	ADJ
fcis-7982	6	44	neural	neural	ADJ
fcis-7982	6	45	network	network	NOUN
fcis-7982	6	46	search	search	NOUN
fcis-7982	6	47	algorithms	algorithm	NOUN
fcis-7982	6	48	.	.	PUNCT
fcis-7982	7	1	the	the	DET
fcis-7982	7	2	results	result	NOUN
fcis-7982	7	3	show	show	VERB
fcis-7982	7	4	that	that	SCONJ
fcis-7982	7	5	the	the	DET
fcis-7982	7	6	improved	improved	ADJ
fcis-7982	7	7	algorithm	algorithm	NOUN
fcis-7982	7	8	can	can	AUX
fcis-7982	7	9	search	search	VERB
fcis-7982	7	10	better	well	ADJ
fcis-7982	7	11	architectures	architecture	NOUN
fcis-7982	7	12	for	for	ADP
fcis-7982	7	13	the	the	DET
fcis-7982	7	14	same	same	ADJ
fcis-7982	7	15	time	time	NOUN
fcis-7982	7	16	when	when	SCONJ
fcis-7982	7	17	experiments	experiment	NOUN
fcis-7982	7	18	are	be	AUX
fcis-7982	7	19	performed	perform	VERB
fcis-7982	7	20	on	on	ADP
fcis-7982	7	21	the	the	DET
fcis-7982	7	22	same	same	ADJ
fcis-7982	7	23	dataset	dataset	NOUN
fcis-7982	7	24	;	;	PUNCT
fcis-7982	7	25	the	the	DET
fcis-7982	7	26	improved	improved	ADJ
fcis-7982	7	27	algorithm	algorithm	NOUN
fcis-7982	7	28	takes	take	VERB
fcis-7982	7	29	less	less	ADJ
fcis-7982	7	30	time	time	NOUN
fcis-7982	7	31	to	to	PART
fcis-7982	7	32	search	search	VERB
fcis-7982	7	33	architectures	architecture	NOUN
fcis-7982	7	34	with	with	ADP
fcis-7982	7	35	similar	similar	ADJ
fcis-7982	7	36	performance	performance	NOUN
fcis-7982	7	37	.	.	PUNCT
fcis-7982	8	1	also	also	ADV
fcis-7982	8	2	,	,	PUNCT
fcis-7982	8	3	the	the	DET
fcis-7982	8	4	improved	improved	ADJ
fcis-7982	8	5	algorithm	algorithm	NOUN
fcis-7982	8	6	searched	search	VERB
fcis-7982	8	7	the	the	DET
fcis-7982	8	8	model	model	NOUN
fcis-7982	8	9	on	on	ADP
fcis-7982	8	10	the	the	DET
fcis-7982	8	11	dataset	dataset	NOUN
fcis-7982	8	12	due	due	ADP
fcis-7982	8	13	to	to	ADP
fcis-7982	8	14	the	the	DET
fcis-7982	8	15	human	human	ADJ
fcis-7982	8	16	optimal	optimal	ADJ
fcis-7982	8	17	level	level	NOUN
fcis-7982	8	18	.	.	PUNCT
fcis-7982	9	1	keywords	keyword	NOUN
fcis-7982	9	2	:	:	PUNCT
fcis-7982	9	3	one	one	NUM
fcis-7982	9	4	-	-	PUNCT
fcis-7982	9	5	shot	shot	NOUN
fcis-7982	9	6	algorithm	algorithm	NOUN
fcis-7982	9	7	;	;	PUNCT
fcis-7982	9	8	weight	weight	NOUN
fcis-7982	9	9	sharing	sharing	NOUN
fcis-7982	9	10	strategy	strategy	NOUN
fcis-7982	9	11	;	;	PUNCT
fcis-7982	9	12	knowledge	knowledge	NOUN
fcis-7982	9	13	graph	graph	NOUN
fcis-7982	9	14	embedding	embed	VERB
fcis-7982	9	15	.	.	PUNCT
fcis-7982	10	1	1	1	X
fcis-7982	10	2	.	.	X
fcis-7982	10	3	introduction	introduction	NOUN
fcis-7982	10	4	knowledge	knowledge	NOUN
fcis-7982	10	5	graph	graph	NOUN
fcis-7982	10	6	(	(	PUNCT
fcis-7982	10	7	kg	kg	X
fcis-7982	10	8	)	)	PUNCT
fcis-7982	10	9	is	be	AUX
fcis-7982	10	10	a	a	DET
fcis-7982	10	11	method	method	NOUN
fcis-7982	10	12	to	to	PART
fcis-7982	10	13	represent	represent	VERB
fcis-7982	10	14	and	and	CCONJ
fcis-7982	10	15	store	store	VERB
fcis-7982	10	16	things	thing	NOUN
fcis-7982	10	17	and	and	CCONJ
fcis-7982	10	18	their	their	PRON
fcis-7982	10	19	relationships	relationship	NOUN
fcis-7982	10	20	through	through	ADP
fcis-7982	10	21	graph	graph	NOUN
fcis-7982	10	22	models	model	NOUN
fcis-7982	10	23	.	.	PUNCT
fcis-7982	11	1	however	however	ADV
fcis-7982	11	2	,	,	PUNCT
fcis-7982	11	3	the	the	DET
fcis-7982	11	4	information	information	NOUN
fcis-7982	11	5	contained	contain	VERB
fcis-7982	11	6	in	in	ADP
fcis-7982	11	7	a	a	DET
fcis-7982	11	8	knowledge	knowledge	NOUN
fcis-7982	11	9	graph	graph	NOUN
fcis-7982	11	10	is	be	AUX
fcis-7982	11	11	often	often	ADV
fcis-7982	11	12	incomplete	incomplete	ADJ
fcis-7982	11	13	,	,	PUNCT
fcis-7982	11	14	and	and	CCONJ
fcis-7982	11	15	as	as	SCONJ
fcis-7982	11	16	knowledge	knowledge	NOUN
fcis-7982	11	17	accumulates	accumulate	VERB
fcis-7982	11	18	,	,	PUNCT
fcis-7982	11	19	many	many	ADJ
fcis-7982	11	20	new	new	ADJ
fcis-7982	11	21	knowledges	knowledge	NOUN
fcis-7982	11	22	will	will	AUX
fcis-7982	11	23	be	be	AUX
fcis-7982	11	24	generated	generate	VERB
fcis-7982	11	25	.	.	PUNCT
fcis-7982	12	1	at	at	ADP
fcis-7982	12	2	this	this	DET
fcis-7982	12	3	time	time	NOUN
fcis-7982	12	4	,	,	PUNCT
fcis-7982	12	5	the	the	DET
fcis-7982	12	6	problems	problem	NOUN
fcis-7982	12	7	of	of	ADP
fcis-7982	12	8	difficult	difficult	ADJ
fcis-7982	12	9	inference	inference	NOUN
fcis-7982	12	10	of	of	ADP
fcis-7982	12	11	the	the	DET
fcis-7982	12	12	relationships	relationship	NOUN
fcis-7982	12	13	between	between	ADP
fcis-7982	12	14	entities	entity	NOUN
fcis-7982	12	15	and	and	CCONJ
fcis-7982	12	16	severe	severe	ADJ
fcis-7982	12	17	data	datum	NOUN
fcis-7982	12	18	sparsity	sparsity	NOUN
fcis-7982	12	19	in	in	ADP
fcis-7982	12	20	knowledge	knowledge	NOUN
fcis-7982	12	21	graphs	graph	NOUN
fcis-7982	12	22	are	be	AUX
fcis-7982	12	23	constantly	constantly	ADV
fcis-7982	12	24	highlighted	highlight	VERB
fcis-7982	12	25	.	.	PUNCT
fcis-7982	13	1	this	this	PRON
fcis-7982	13	2	brings	bring	VERB
fcis-7982	13	3	inconvenience	inconvenience	NOUN
fcis-7982	13	4	to	to	ADP
fcis-7982	13	5	the	the	DET
fcis-7982	13	6	further	further	ADJ
fcis-7982	13	7	application	application	NOUN
fcis-7982	13	8	of	of	ADP
fcis-7982	13	9	knowledge	knowledge	NOUN
fcis-7982	13	10	graphs	graph	NOUN
fcis-7982	13	11	in	in	ADP
fcis-7982	13	12	industrial	industrial	ADJ
fcis-7982	13	13	production	production	NOUN
fcis-7982	13	14	.	.	PUNCT
fcis-7982	14	1	in	in	ADP
fcis-7982	14	2	recent	recent	ADJ
fcis-7982	14	3	years	year	NOUN
fcis-7982	14	4	,	,	PUNCT
fcis-7982	14	5	knowledge	knowledge	NOUN
fcis-7982	14	6	graph	graph	NOUN
fcis-7982	14	7	embedding	embed	VERB
fcis-7982	14	8	(	(	PUNCT
fcis-7982	14	9	kge	kge	NOUN
fcis-7982	14	10	)	)	PUNCT
fcis-7982	14	11	,	,	PUNCT
fcis-7982	14	12	which	which	PRON
fcis-7982	14	13	is	be	AUX
fcis-7982	14	14	the	the	DET
fcis-7982	14	15	core	core	NOUN
fcis-7982	14	16	technology	technology	NOUN
fcis-7982	14	17	of	of	ADP
fcis-7982	14	18	knowledge	knowledge	NOUN
fcis-7982	14	19	representation	representation	NOUN
fcis-7982	14	20	,	,	PUNCT
fcis-7982	14	21	has	have	AUX
fcis-7982	14	22	made	make	VERB
fcis-7982	14	23	new	new	ADJ
fcis-7982	14	24	research	research	NOUN
fcis-7982	14	25	breakthroughs	breakthrough	NOUN
fcis-7982	14	26	,	,	PUNCT
fcis-7982	14	27	and	and	CCONJ
fcis-7982	14	28	the	the	DET
fcis-7982	14	29	main	main	ADJ
fcis-7982	14	30	technical	technical	ADJ
fcis-7982	14	31	implementation	implementation	NOUN
fcis-7982	14	32	route	route	NOUN
fcis-7982	14	33	of	of	ADP
fcis-7982	14	34	kge	kge	NOUN
fcis-7982	14	35	is	be	AUX
fcis-7982	14	36	to	to	PART
fcis-7982	14	37	use	use	VERB
fcis-7982	14	38	the	the	DET
fcis-7982	14	39	translation	translation	NOUN
fcis-7982	14	40	invariance	invariance	NOUN
fcis-7982	14	41	of	of	ADP
fcis-7982	14	42	word	word	NOUN
fcis-7982	14	43	vectors	vector	NOUN
fcis-7982	14	44	to	to	PART
fcis-7982	14	45	embed	embed	VERB
fcis-7982	14	46	the	the	DET
fcis-7982	14	47	high	high	ADJ
fcis-7982	14	48	-	-	PUNCT
fcis-7982	14	49	dimensional	dimensional	ADJ
fcis-7982	14	50	entities	entity	NOUN
fcis-7982	14	51	and	and	CCONJ
fcis-7982	14	52	relations	relation	NOUN
fcis-7982	14	53	in	in	ADP
fcis-7982	14	54	the	the	DET
fcis-7982	14	55	knowledge	knowledge	NOUN
fcis-7982	14	56	graph	graph	NOUN
fcis-7982	14	57	into	into	ADP
fcis-7982	14	58	the	the	DET
fcis-7982	14	59	lowdimensional	lowdimensional	ADJ
fcis-7982	14	60	vector	vector	NOUN
fcis-7982	14	61	space	space	NOUN
fcis-7982	14	62	,	,	PUNCT
fcis-7982	14	63	so	so	SCONJ
fcis-7982	14	64	that	that	SCONJ
fcis-7982	14	65	the	the	DET
fcis-7982	14	66	semantic	semantic	ADJ
fcis-7982	14	67	reasoning	reasoning	NOUN
fcis-7982	14	68	process	process	NOUN
fcis-7982	14	69	of	of	ADP
fcis-7982	14	70	entities	entity	NOUN
fcis-7982	14	71	and	and	CCONJ
fcis-7982	14	72	relations	relation	NOUN
fcis-7982	14	73	can	can	AUX
fcis-7982	14	74	be	be	AUX
fcis-7982	14	75	converts	convert	NOUN
fcis-7982	14	76	the	the	DET
fcis-7982	14	77	semantic	semantic	ADJ
fcis-7982	14	78	inference	inference	NOUN
fcis-7982	14	79	process	process	NOUN
fcis-7982	14	80	of	of	ADP
fcis-7982	14	81	entities	entity	NOUN
fcis-7982	14	82	and	and	CCONJ
fcis-7982	14	83	relations	relation	NOUN
fcis-7982	14	84	into	into	ADP
fcis-7982	14	85	the	the	DET
fcis-7982	14	86	computation	computation	NOUN
fcis-7982	14	87	of	of	ADP
fcis-7982	14	88	distances	distance	NOUN
fcis-7982	14	89	between	between	ADP
fcis-7982	14	90	objects	object	NOUN
fcis-7982	14	91	in	in	ADP
fcis-7982	14	92	the	the	DET
fcis-7982	14	93	vector	vector	NOUN
fcis-7982	14	94	space	space	NOUN
fcis-7982	14	95	.	.	PUNCT
fcis-7982	15	1	the	the	DET
fcis-7982	15	2	interstellar	interstellar	NOUN
fcis-7982	15	3	[	[	X
fcis-7982	15	4	6	6	NUM
fcis-7982	15	5	]	]	PUNCT
fcis-7982	15	6	algorithm	algorithm	NOUN
fcis-7982	15	7	greatly	greatly	ADV
fcis-7982	15	8	improves	improve	VERB
fcis-7982	15	9	the	the	DET
fcis-7982	15	10	search	search	NOUN
fcis-7982	15	11	efficiency	efficiency	NOUN
fcis-7982	15	12	of	of	ADP
fcis-7982	15	13	nas	nas	PROPN
fcis-7982	15	14	and	and	CCONJ
fcis-7982	15	15	the	the	DET
fcis-7982	15	16	performance	performance	NOUN
fcis-7982	15	17	of	of	ADP
fcis-7982	15	18	searching	search	VERB
fcis-7982	15	19	to	to	ADP
fcis-7982	15	20	architectures	architecture	NOUN
fcis-7982	15	21	.	.	PUNCT
fcis-7982	16	1	however	however	ADV
fcis-7982	16	2	,	,	PUNCT
fcis-7982	16	3	the	the	DET
fcis-7982	16	4	interstellar	interstellar	ADJ
fcis-7982	16	5	algorithm	algorithm	NOUN
fcis-7982	16	6	initializes	initialize	VERB
fcis-7982	16	7	the	the	DET
fcis-7982	16	8	microarchitecture	microarchitecture	NOUN
fcis-7982	16	9	parameter	parameter	NOUN
fcis-7982	16	10	probability	probability	NOUN
fcis-7982	16	11	distribution	distribution	NOUN
fcis-7982	16	12	matrix	matrix	NOUN
fcis-7982	16	13	by	by	ADP
fcis-7982	16	14	taking	take	VERB
fcis-7982	16	15	the	the	DET
fcis-7982	16	16	mean	mean	ADJ
fcis-7982	16	17	value	value	NOUN
fcis-7982	16	18	when	when	SCONJ
fcis-7982	16	19	searching	search	VERB
fcis-7982	16	20	for	for	ADP
fcis-7982	16	21	the	the	DET
fcis-7982	16	22	corresponding	corresponding	ADJ
fcis-7982	16	23	microarchitecture	microarchitecture	NOUN
fcis-7982	16	24	for	for	ADP
fcis-7982	16	25	each	each	DET
fcis-7982	16	26	microarchitecture	microarchitecture	NOUN
fcis-7982	16	27	.	.	PUNCT
fcis-7982	17	1	this	this	DET
fcis-7982	17	2	algorithm	algorithm	NOUN
fcis-7982	17	3	design	design	NOUN
fcis-7982	17	4	makes	make	VERB
fcis-7982	17	5	it	it	PRON
fcis-7982	17	6	difficult	difficult	ADJ
fcis-7982	17	7	to	to	PART
fcis-7982	17	8	reuse	reuse	VERB
fcis-7982	17	9	the	the	DET
fcis-7982	17	10	information	information	NOUN
fcis-7982	17	11	related	relate	VERB
fcis-7982	17	12	to	to	ADP
fcis-7982	17	13	the	the	DET
fcis-7982	17	14	microarchitecture	microarchitecture	NOUN
fcis-7982	17	15	learned	learn	VERB
fcis-7982	17	16	in	in	ADP
fcis-7982	17	17	each	each	DET
fcis-7982	17	18	round	round	NOUN
fcis-7982	17	19	.	.	PUNCT
fcis-7982	18	1	considering	consider	VERB
fcis-7982	18	2	that	that	SCONJ
fcis-7982	18	3	the	the	DET
fcis-7982	18	4	microarchitecture	microarchitecture	NOUN
fcis-7982	18	5	is	be	AUX
fcis-7982	18	6	a	a	DET
fcis-7982	18	7	supernet	supernet	NOUN
fcis-7982	18	8	with	with	ADP
fcis-7982	18	9	shared	share	VERB
fcis-7982	18	10	parameters	parameter	NOUN
fcis-7982	18	11	,	,	PUNCT
fcis-7982	18	12	a	a	DET
fcis-7982	18	13	one	one	NUM
fcis-7982	18	14	-	-	PUNCT
fcis-7982	18	15	time	time	NOUN
fcis-7982	18	16	evaluation	evaluation	NOUN
fcis-7982	18	17	strategy	strategy	NOUN
fcis-7982	18	18	is	be	AUX
fcis-7982	18	19	used	use	VERB
fcis-7982	18	20	.	.	PUNCT
fcis-7982	19	1	inspired	inspire	VERB
fcis-7982	19	2	by	by	ADP
fcis-7982	19	3	this	this	PRON
fcis-7982	19	4	,	,	PUNCT
fcis-7982	19	5	we	we	PRON
fcis-7982	19	6	consider	consider	VERB
fcis-7982	19	7	using	use	VERB
fcis-7982	19	8	the	the	DET
fcis-7982	19	9	probability	probability	NOUN
fcis-7982	19	10	distribution	distribution	NOUN
fcis-7982	19	11	matrix	matrix	NOUN
fcis-7982	19	12	of	of	ADP
fcis-7982	19	13	microarchitecture	microarchitecture	NOUN
fcis-7982	19	14	parameters	parameter	NOUN
fcis-7982	19	15	updated	update	VERB
fcis-7982	19	16	in	in	ADP
fcis-7982	19	17	the	the	DET
fcis-7982	19	18	previous	previous	ADJ
fcis-7982	19	19	round	round	NOUN
fcis-7982	19	20	to	to	PART
fcis-7982	19	21	initialize	initialize	VERB
fcis-7982	19	22	the	the	DET
fcis-7982	19	23	information	information	NOUN
fcis-7982	19	24	for	for	ADP
fcis-7982	19	25	the	the	DET
fcis-7982	19	26	next	next	ADJ
fcis-7982	19	27	round	round	NOUN
fcis-7982	19	28	to	to	PART
fcis-7982	19	29	better	well	ADV
fcis-7982	19	30	utilize	utilize	VERB
fcis-7982	19	31	the	the	DET
fcis-7982	19	32	information	information	NOUN
fcis-7982	19	33	from	from	ADP
fcis-7982	19	34	the	the	DET
fcis-7982	19	35	previous	previous	ADJ
fcis-7982	19	36	round	round	NOUN
fcis-7982	19	37	and	and	CCONJ
fcis-7982	19	38	improve	improve	VERB
fcis-7982	19	39	the	the	DET
fcis-7982	19	40	search	search	NOUN
fcis-7982	19	41	efficiency	efficiency	NOUN
fcis-7982	19	42	.	.	PUNCT
fcis-7982	20	1	in	in	ADP
fcis-7982	20	2	this	this	DET
fcis-7982	20	3	paper	paper	NOUN
fcis-7982	20	4	,	,	PUNCT
fcis-7982	20	5	we	we	PRON
fcis-7982	20	6	first	first	ADV
fcis-7982	20	7	introduce	introduce	VERB
fcis-7982	20	8	the	the	DET
fcis-7982	20	9	current	current	ADJ
fcis-7982	20	10	research	research	NOUN
fcis-7982	20	11	status	status	NOUN
fcis-7982	20	12	of	of	ADP
fcis-7982	20	13	algorithm	algorithm	NOUN
fcis-7982	20	14	-	-	PUNCT
fcis-7982	20	15	related	relate	VERB
fcis-7982	20	16	theories	theory	NOUN
fcis-7982	20	17	,	,	PUNCT
fcis-7982	20	18	next	next	ADJ
fcis-7982	20	19	introduce	introduce	VERB
fcis-7982	20	20	the	the	DET
fcis-7982	20	21	idea	idea	NOUN
fcis-7982	20	22	of	of	ADP
fcis-7982	20	23	search	search	NOUN
fcis-7982	20	24	space	space	NOUN
fcis-7982	20	25	partitioning	partitioning	NOUN
fcis-7982	20	26	,	,	PUNCT
fcis-7982	20	27	and	and	CCONJ
fcis-7982	20	28	provide	provide	VERB
fcis-7982	20	29	a	a	DET
fcis-7982	20	30	specific	specific	ADJ
fcis-7982	20	31	description	description	NOUN
fcis-7982	20	32	of	of	ADP
fcis-7982	20	33	algorithm	algorithm	NOUN
fcis-7982	20	34	improvement	improvement	NOUN
fcis-7982	20	35	,	,	PUNCT
fcis-7982	20	36	ideas	idea	NOUN
fcis-7982	20	37	and	and	CCONJ
fcis-7982	20	38	algorithm	algorithm	NOUN
fcis-7982	20	39	flow	flow	NOUN
fcis-7982	20	40	,	,	PUNCT
fcis-7982	20	41	and	and	CCONJ
fcis-7982	20	42	describe	describe	VERB
fcis-7982	20	43	the	the	DET
fcis-7982	20	44	analysis	analysis	NOUN
fcis-7982	20	45	of	of	ADP
fcis-7982	20	46	experimental	experimental	ADJ
fcis-7982	20	47	setup	setup	NOUN
fcis-7982	20	48	and	and	CCONJ
fcis-7982	20	49	experimental	experimental	ADJ
fcis-7982	20	50	results	result	NOUN
fcis-7982	20	51	.	.	PUNCT
fcis-7982	21	1	the	the	DET
fcis-7982	21	2	performance	performance	NOUN
fcis-7982	21	3	of	of	ADP
fcis-7982	21	4	the	the	DET
fcis-7982	21	5	improved	improved	ADJ
fcis-7982	21	6	algorithm	algorithm	NOUN
fcis-7982	21	7	is	be	AUX
fcis-7982	21	8	compared	compare	VERB
fcis-7982	21	9	with	with	ADP
fcis-7982	21	10	the	the	DET
fcis-7982	21	11	architecture	architecture	NOUN
fcis-7982	21	12	searched	search	VERB
fcis-7982	21	13	by	by	ADP
fcis-7982	21	14	the	the	DET
fcis-7982	21	15	original	original	ADJ
fcis-7982	21	16	algorithm	algorithm	NOUN
fcis-7982	21	17	and	and	CCONJ
fcis-7982	21	18	the	the	DET
fcis-7982	21	19	excellent	excellent	ADJ
fcis-7982	21	20	architecture	architecture	NOUN
fcis-7982	21	21	designed	design	VERB
fcis-7982	21	22	by	by	ADP
fcis-7982	21	23	human	human	ADJ
fcis-7982	21	24	hand	hand	NOUN
fcis-7982	21	25	,	,	PUNCT
fcis-7982	21	26	and	and	CCONJ
fcis-7982	21	27	finally	finally	ADV
fcis-7982	21	28	a	a	DET
fcis-7982	21	29	summary	summary	NOUN
fcis-7982	21	30	and	and	CCONJ
fcis-7982	21	31	a	a	DET
fcis-7982	21	32	discussion	discussion	NOUN
fcis-7982	21	33	of	of	ADP
fcis-7982	21	34	future	future	ADJ
fcis-7982	21	35	work	work	NOUN
fcis-7982	21	36	are	be	AUX
fcis-7982	21	37	given	give	VERB
fcis-7982	21	38	.	.	PUNCT
fcis-7982	22	1	2	2	X
fcis-7982	22	2	.	.	X
fcis-7982	22	3	related	relate	VERB
fcis-7982	22	4	work	work	NOUN
fcis-7982	22	5	2.1	2.1	NUM
fcis-7982	22	6	.	.	PUNCT
fcis-7982	23	1	knowledge	knowledge	NOUN
fcis-7982	23	2	graph	graph	NOUN
fcis-7982	23	3	embedding	embed	VERB
fcis-7982	23	4	(	(	PUNCT
fcis-7982	23	5	kge	kge	NOUN
fcis-7982	23	6	)	)	PUNCT
fcis-7982	23	7	the	the	DET
fcis-7982	23	8	main	main	ADJ
fcis-7982	23	9	research	research	NOUN
fcis-7982	23	10	objective	objective	NOUN
fcis-7982	23	11	of	of	ADP
fcis-7982	23	12	the	the	DET
fcis-7982	23	13	kge	kge	ADJ
fcis-7982	23	14	task	task	NOUN
fcis-7982	23	15	is	be	AUX
fcis-7982	23	16	to	to	PART
fcis-7982	23	17	map	map	VERB
fcis-7982	23	18	the	the	DET
fcis-7982	23	19	entities	entity	NOUN
fcis-7982	23	20	and	and	CCONJ
fcis-7982	23	21	their	their	PRON
fcis-7982	23	22	relations	relation	NOUN
fcis-7982	23	23	in	in	ADP
fcis-7982	23	24	a	a	DET
fcis-7982	23	25	knowledge	knowledge	NOUN
fcis-7982	23	26	graph	graph	NOUN
fcis-7982	23	27	representing	represent	VERB
fcis-7982	23	28	a	a	DET
fcis-7982	23	29	high	high	ADJ
fcis-7982	23	30	-	-	PUNCT
fcis-7982	23	31	dimensional	dimensional	ADJ
fcis-7982	23	32	space	space	NOUN
fcis-7982	23	33	one	one	NUM
fcis-7982	23	34	by	by	ADP
fcis-7982	23	35	one	one	NUM
fcis-7982	23	36	into	into	ADP
fcis-7982	23	37	a	a	DET
fcis-7982	23	38	low	low	ADJ
fcis-7982	23	39	-	-	PUNCT
fcis-7982	23	40	dimensional	dimensional	ADJ
fcis-7982	23	41	continuous	continuous	ADJ
fcis-7982	23	42	vector	vector	NOUN
fcis-7982	23	43	space	space	NOUN
fcis-7982	23	44	,	,	PUNCT
fcis-7982	23	45	which	which	PRON
fcis-7982	23	46	is	be	AUX
fcis-7982	23	47	also	also	ADV
fcis-7982	23	48	called	call	VERB
fcis-7982	23	49	representation	representation	NOUN
fcis-7982	23	50	learning	learning	NOUN
fcis-7982	23	51	in	in	ADP
fcis-7982	23	52	knowledge	knowledge	NOUN
fcis-7982	23	53	(	(	PUNCT
fcis-7982	23	54	rlk	rlk	VERB
fcis-7982	23	55	)	)	PUNCT
fcis-7982	23	56	.	.	PUNCT
fcis-7982	24	1	a	a	DET
fcis-7982	24	2	knowledge	knowledge	NOUN
fcis-7982	24	3	graph	graph	NOUN
fcis-7982	24	4	is	be	AUX
fcis-7982	24	5	composed	compose	VERB
fcis-7982	24	6	of	of	ADP
fcis-7982	24	7	a	a	DET
fcis-7982	24	8	triad	triad	ADJ
fcis-7982	24	9	representing	represent	VERB
fcis-7982	24	10	entities	entity	NOUN
fcis-7982	24	11	and	and	CCONJ
fcis-7982	24	12	relationships	relationship	NOUN
fcis-7982	24	13	.	.	PUNCT
fcis-7982	25	1	therefore	therefore	ADV
fcis-7982	25	2	,	,	PUNCT
fcis-7982	25	3	kge	kge	ADJ
fcis-7982	25	4	models	model	NOUN
fcis-7982	25	5	can	can	AUX
fcis-7982	25	6	be	be	AUX
fcis-7982	25	7	divided	divide	VERB
fcis-7982	25	8	into	into	ADP
fcis-7982	25	9	triplet	triplet	NOUN
fcis-7982	25	10	-	-	PUNCT
fcis-7982	25	11	based	base	VERB
fcis-7982	25	12	models	model	NOUN
fcis-7982	25	13	and	and	CCONJ
fcis-7982	25	14	path	path	NOUN
fcis-7982	25	15	-	-	PUNCT
fcis-7982	25	16	based	base	VERB
fcis-7982	25	17	models	model	NOUN
fcis-7982	25	18	.	.	PUNCT
fcis-7982	26	1	in	in	ADP
fcis-7982	26	2	terms	term	NOUN
fcis-7982	26	3	of	of	ADP
fcis-7982	26	4	organization	organization	NOUN
fcis-7982	26	5	,	,	PUNCT
fcis-7982	26	6	knowledge	knowledge	NOUN
fcis-7982	26	7	graphs	graph	NOUN
fcis-7982	26	8	are	be	AUX
fcis-7982	26	9	complex	complex	ADJ
fcis-7982	26	10	network	network	NOUN
fcis-7982	26	11	structures	structure	NOUN
fcis-7982	26	12	consisting	consist	VERB
fcis-7982	26	13	of	of	ADP
fcis-7982	26	14	entities	entity	NOUN
fcis-7982	26	15	and	and	CCONJ
fcis-7982	26	16	relationships	relationship	NOUN
fcis-7982	26	17	,	,	PUNCT
fcis-7982	26	18	and	and	CCONJ
fcis-7982	26	19	researchers	researcher	NOUN
fcis-7982	26	20	have	have	AUX
fcis-7982	26	21	also	also	ADV
fcis-7982	26	22	proposed	propose	VERB
fcis-7982	26	23	some	some	DET
fcis-7982	26	24	graph	graph	NOUN
fcis-7982	26	25	-	-	PUNCT
fcis-7982	26	26	based	base	VERB
fcis-7982	26	27	models	model	NOUN
fcis-7982	26	28	(	(	PUNCT
fcis-7982	26	29	gcn	gcn	NOUN
fcis-7982	26	30	-	-	PUNCT
fcis-7982	26	31	based	base	VERB
fcis-7982	26	32	)	)	PUNCT
fcis-7982	26	33	.	.	PUNCT
fcis-7982	27	1	triplet	triplet	NOUN
fcis-7982	27	2	-	-	PUNCT
fcis-7982	27	3	based	base	VERB
fcis-7982	27	4	models	model	NOUN
fcis-7982	27	5	interpret	interpret	VERB
fcis-7982	27	6	the	the	DET
fcis-7982	27	7	interactions	interaction	NOUN
fcis-7982	27	8	between	between	ADP
fcis-7982	27	9	triads	triad	NOUN
fcis-7982	27	10	in	in	ADP
fcis-7982	27	11	a	a	DET
fcis-7982	27	12	different	different	ADJ
fcis-7982	27	13	way	way	NOUN
fcis-7982	27	14	,	,	PUNCT
fcis-7982	27	15	path	path	NOUN
fcis-7982	27	16	-	-	PUNCT
fcis-7982	27	17	based	base	VERB
fcis-7982	27	18	models	model	NOUN
fcis-7982	27	19	can	can	AUX
fcis-7982	27	20	learn	learn	VERB
fcis-7982	27	21	both	both	DET
fcis-7982	27	22	relations	relation	NOUN
fcis-7982	27	23	and	and	CCONJ
fcis-7982	27	24	entities	entity	NOUN
fcis-7982	27	25	and	and	CCONJ
fcis-7982	27	26	relations	relation	NOUN
fcis-7982	27	27	on	on	ADP
fcis-7982	27	28	the	the	DET
fcis-7982	27	29	path	path	NOUN
fcis-7982	27	30	,	,	PUNCT
fcis-7982	27	31	and	and	CCONJ
fcis-7982	27	32	graph	graph	NOUN
fcis-7982	27	33	-	-	PUNCT
fcis-7982	27	34	based	base	VERB
fcis-7982	27	35	models	model	NOUN
fcis-7982	27	36	can	can	AUX
fcis-7982	27	37	make	make	VERB
fcis-7982	27	38	full	full	ADJ
fcis-7982	27	39	use	use	NOUN
fcis-7982	27	40	of	of	ADP
fcis-7982	27	41	graph	graph	NOUN
fcis-7982	27	42	structure	structure	NOUN
fcis-7982	27	43	features	feature	NOUN
fcis-7982	27	44	to	to	PART
fcis-7982	27	45	provide	provide	VERB
fcis-7982	27	46	more	more	ADV
fcis-7982	27	47	accurate	accurate	ADJ
fcis-7982	27	48	and	and	CCONJ
fcis-7982	27	49	explanatory	explanatory	ADJ
fcis-7982	27	50	semantic	semantic	ADJ
fcis-7982	27	51	embeddings	embedding	NOUN
fcis-7982	27	52	for	for	ADP
fcis-7982	27	53	entities	entity	NOUN
fcis-7982	27	54	and	and	CCONJ
fcis-7982	27	55	relations	relation	NOUN
fcis-7982	27	56	.	.	PUNCT
fcis-7982	28	1	2.2	2.2	NUM
fcis-7982	28	2	.	.	PUNCT
fcis-7982	28	3	neural	neural	ADJ
fcis-7982	28	4	architecture	architecture	NOUN
fcis-7982	28	5	search	search	NOUN
fcis-7982	28	6	(	(	PUNCT
fcis-7982	28	7	nas	nas	PROPN
fcis-7982	28	8	)	)	PUNCT
fcis-7982	28	9	with	with	ADP
fcis-7982	28	10	the	the	DET
fcis-7982	28	11	success	success	NOUN
fcis-7982	28	12	of	of	ADP
fcis-7982	28	13	deep	deep	ADJ
fcis-7982	28	14	learning	learning	NOUN
fcis-7982	28	15	,	,	PUNCT
fcis-7982	28	16	neural	neural	ADJ
fcis-7982	28	17	networks	network	NOUN
fcis-7982	28	18	are	be	AUX
fcis-7982	28	19	used	use	VERB
fcis-7982	28	20	in	in	ADP
fcis-7982	28	21	more	more	ADJ
fcis-7982	28	22	and	and	CCONJ
fcis-7982	28	23	more	more	ADJ
fcis-7982	28	24	fields	field	NOUN
fcis-7982	28	25	,	,	PUNCT
fcis-7982	28	26	different	different	ADJ
fcis-7982	28	27	network	network	NOUN
fcis-7982	28	28	architectures	architecture	NOUN
fcis-7982	28	29	are	be	AUX
fcis-7982	28	30	developed	develop	VERB
fcis-7982	28	31	and	and	CCONJ
fcis-7982	28	32	applied	apply	VERB
fcis-7982	28	33	to	to	ADP
fcis-7982	28	34	different	different	ADJ
fcis-7982	28	35	fields	field	NOUN
fcis-7982	28	36	,	,	PUNCT
fcis-7982	28	37	neural	neural	ADJ
fcis-7982	28	38	networks	network	NOUN
fcis-7982	28	39	become	become	VERB
fcis-7982	28	40	more	more	ADV
fcis-7982	28	41	and	and	CCONJ
fcis-7982	28	42	more	more	ADV
fcis-7982	28	43	complex	complex	ADJ
fcis-7982	28	44	,	,	PUNCT
fcis-7982	28	45	and	and	CCONJ
fcis-7982	28	46	the	the	DET
fcis-7982	28	47	difficulty	difficulty	NOUN
fcis-7982	28	48	of	of	ADP
fcis-7982	28	49	designing	design	VERB
fcis-7982	28	50	neural	neural	ADJ
fcis-7982	28	51	networks	network	NOUN
fcis-7982	28	52	manually	manually	ADV
fcis-7982	28	53	is	be	AUX
fcis-7982	28	54	increasing	increase	VERB
fcis-7982	28	55	.	.	PUNCT
fcis-7982	29	1	the	the	DET
fcis-7982	29	2	2	2	NUM
fcis-7982	29	3	concept	concept	NOUN
fcis-7982	29	4	of	of	ADP
fcis-7982	29	5	neural	neural	ADJ
fcis-7982	29	6	architecture	architecture	NOUN
fcis-7982	29	7	search	search	NOUN
fcis-7982	29	8	(	(	PUNCT
fcis-7982	29	9	nas	nas	PROPN
fcis-7982	29	10	)	)	PUNCT
fcis-7982	29	11	was	be	AUX
fcis-7982	29	12	first	first	ADV
fcis-7982	29	13	introduced	introduce	VERB
fcis-7982	29	14	in	in	ADP
fcis-7982	29	15	2017.nas	2017.nas	PROPN
fcis-7982	29	16	focuses	focus	VERB
fcis-7982	29	17	on	on	ADP
fcis-7982	29	18	how	how	SCONJ
fcis-7982	29	19	to	to	PART
fcis-7982	29	20	make	make	VERB
fcis-7982	29	21	machines	machine	NOUN
fcis-7982	29	22	automatically	automatically	ADV
fcis-7982	29	23	search	search	VERB
fcis-7982	29	24	for	for	ADP
fcis-7982	29	25	neural	neural	ADJ
fcis-7982	29	26	networks	network	NOUN
fcis-7982	29	27	with	with	ADP
fcis-7982	29	28	better	well	ADJ
fcis-7982	29	29	performance	performance	NOUN
fcis-7982	29	30	faster	fast	ADV
fcis-7982	29	31	.	.	PUNCT
fcis-7982	30	1	currently	currently	ADV
fcis-7982	30	2	,	,	PUNCT
fcis-7982	30	3	neural	neural	ADJ
fcis-7982	30	4	networks	network	NOUN
fcis-7982	30	5	built	build	VERB
fcis-7982	30	6	using	use	VERB
fcis-7982	30	7	nas	nas	PROPN
fcis-7982	30	8	methods	method	NOUN
fcis-7982	30	9	have	have	AUX
fcis-7982	30	10	outperformed	outperform	VERB
fcis-7982	30	11	neural	neural	ADJ
fcis-7982	30	12	networks	network	NOUN
fcis-7982	30	13	designed	design	VERB
fcis-7982	30	14	by	by	ADP
fcis-7982	30	15	humans	human	NOUN
fcis-7982	30	16	on	on	ADP
fcis-7982	30	17	these	these	DET
fcis-7982	30	18	tasks	task	NOUN
fcis-7982	30	19	for	for	ADP
fcis-7982	30	20	tasks	task	NOUN
fcis-7982	30	21	such	such	ADJ
fcis-7982	30	22	as	as	ADP
fcis-7982	30	23	image	image	NOUN
fcis-7982	30	24	classification	classification	NOUN
fcis-7982	30	25	,	,	PUNCT
fcis-7982	30	26	target	target	NOUN
fcis-7982	30	27	detection	detection	NOUN
fcis-7982	30	28	,	,	PUNCT
fcis-7982	30	29	and	and	CCONJ
fcis-7982	30	30	semantic	semantic	ADJ
fcis-7982	30	31	segmentation	segmentation	NOUN
fcis-7982	30	32	.	.	PUNCT
fcis-7982	31	1	there	there	PRON
fcis-7982	31	2	are	be	VERB
fcis-7982	31	3	three	three	NUM
fcis-7982	31	4	main	main	ADJ
fcis-7982	31	5	research	research	NOUN
fcis-7982	31	6	directions	direction	NOUN
fcis-7982	31	7	of	of	ADP
fcis-7982	31	8	nas	nas	NOUN
fcis-7982	32	1	[	[	X
fcis-7982	32	2	2	2	NUM
fcis-7982	32	3	]	]	PUNCT
fcis-7982	32	4	:	:	PUNCT
fcis-7982	32	5	how	how	SCONJ
fcis-7982	32	6	to	to	PART
fcis-7982	32	7	construct	construct	VERB
fcis-7982	32	8	a	a	DET
fcis-7982	32	9	complete	complete	ADJ
fcis-7982	32	10	and	and	CCONJ
fcis-7982	32	11	efficient	efficient	ADJ
fcis-7982	32	12	search	search	NOUN
fcis-7982	32	13	space	space	NOUN
fcis-7982	32	14	,	,	PUNCT
fcis-7982	32	15	how	how	SCONJ
fcis-7982	32	16	to	to	PART
fcis-7982	32	17	search	search	VERB
fcis-7982	32	18	neural	neural	ADJ
fcis-7982	32	19	networks	network	NOUN
fcis-7982	32	20	quickly	quickly	ADV
fcis-7982	32	21	,	,	PUNCT
fcis-7982	32	22	and	and	CCONJ
fcis-7982	32	23	how	how	SCONJ
fcis-7982	32	24	to	to	PART
fcis-7982	32	25	evaluate	evaluate	VERB
fcis-7982	32	26	the	the	DET
fcis-7982	32	27	performance	performance	NOUN
fcis-7982	32	28	of	of	ADP
fcis-7982	32	29	the	the	DET
fcis-7982	32	30	searched	search	VERB
fcis-7982	32	31	neural	neural	ADJ
fcis-7982	32	32	networks	network	NOUN
fcis-7982	32	33	more	more	ADV
fcis-7982	32	34	scientifically	scientifically	ADV
fcis-7982	32	35	.	.	PUNCT
fcis-7982	33	1	the	the	DET
fcis-7982	33	2	relationship	relationship	NOUN
fcis-7982	33	3	between	between	ADP
fcis-7982	33	4	the	the	DET
fcis-7982	33	5	search	search	NOUN
fcis-7982	33	6	space	space	NOUN
fcis-7982	33	7	,	,	PUNCT
fcis-7982	33	8	search	search	NOUN
fcis-7982	33	9	strategy	strategy	NOUN
fcis-7982	33	10	,	,	PUNCT
fcis-7982	33	11	and	and	CCONJ
fcis-7982	33	12	performance	performance	NOUN
fcis-7982	33	13	evaluation	evaluation	NOUN
fcis-7982	33	14	strategy	strategy	NOUN
fcis-7982	33	15	is	be	AUX
fcis-7982	33	16	shown	show	VERB
fcis-7982	33	17	in	in	ADP
fcis-7982	33	18	figure	figure	NOUN
fcis-7982	33	19	1	1	NUM
fcis-7982	33	20	.	.	PUNCT
fcis-7982	33	21	figure	figure	NOUN
fcis-7982	33	22	1	1	NUM
fcis-7982	33	23	.	.	NOUN
fcis-7982	33	24	example	example	NOUN
fcis-7982	33	25	of	of	ADP
fcis-7982	33	26	a	a	DET
fcis-7982	33	27	generic	generic	ADJ
fcis-7982	33	28	nas	nas	NOUN
fcis-7982	33	29	algorithm	algorithm	NOUN
fcis-7982	33	30	idea	idea	NOUN
fcis-7982	33	31	the	the	DET
fcis-7982	33	32	search	search	NOUN
fcis-7982	33	33	strategy	strategy	NOUN
fcis-7982	33	34	selects	select	VERB
fcis-7982	33	35	one	one	NUM
fcis-7982	33	36	or	or	CCONJ
fcis-7982	33	37	several	several	ADJ
fcis-7982	33	38	architectures	architecture	NOUN
fcis-7982	33	39	from	from	ADP
fcis-7982	33	40	a	a	DET
fcis-7982	33	41	predefined	predefine	VERB
fcis-7982	33	42	search	search	NOUN
fcis-7982	33	43	space	space	NOUN
fcis-7982	33	44	a.	a.	NOUN
fcis-7982	33	45	these	these	DET
fcis-7982	33	46	architectures	architecture	NOUN
fcis-7982	33	47	are	be	AUX
fcis-7982	33	48	passed	pass	VERB
fcis-7982	33	49	to	to	ADP
fcis-7982	33	50	the	the	DET
fcis-7982	33	51	performance	performance	NOUN
fcis-7982	33	52	evaluation	evaluation	NOUN
fcis-7982	33	53	module	module	NOUN
fcis-7982	33	54	,	,	PUNCT
fcis-7982	33	55	which	which	PRON
fcis-7982	33	56	feeds	feed	VERB
fcis-7982	33	57	the	the	DET
fcis-7982	33	58	performance	performance	NOUN
fcis-7982	33	59	evaluation	evaluation	NOUN
fcis-7982	33	60	scores	score	NOUN
fcis-7982	33	61	of	of	ADP
fcis-7982	33	62	these	these	DET
fcis-7982	33	63	architectures	architecture	NOUN
fcis-7982	33	64	to	to	ADP
fcis-7982	33	65	the	the	DET
fcis-7982	33	66	search	search	NOUN
fcis-7982	33	67	strategy	strategy	NOUN
fcis-7982	33	68	to	to	PART
fcis-7982	33	69	guide	guide	VERB
fcis-7982	33	70	the	the	DET
fcis-7982	33	71	optimization	optimization	NOUN
fcis-7982	33	72	of	of	ADP
fcis-7982	33	73	the	the	DET
fcis-7982	33	74	next	next	ADJ
fcis-7982	33	75	search	search	NOUN
fcis-7982	33	76	.	.	PUNCT
fcis-7982	34	1	we	we	PRON
fcis-7982	34	2	first	first	ADV
fcis-7982	34	3	consider	consider	VERB
fcis-7982	34	4	the	the	DET
fcis-7982	34	5	search	search	NOUN
fcis-7982	34	6	space	space	NOUN
fcis-7982	34	7	,	,	PUNCT
fcis-7982	34	8	which	which	PRON
fcis-7982	34	9	should	should	AUX
fcis-7982	34	10	be	be	AUX
fcis-7982	34	11	complete	complete	ADJ
fcis-7982	34	12	so	so	SCONJ
fcis-7982	34	13	as	as	SCONJ
fcis-7982	34	14	to	to	PART
fcis-7982	34	15	ensure	ensure	VERB
fcis-7982	34	16	that	that	SCONJ
fcis-7982	34	17	the	the	DET
fcis-7982	34	18	search	search	NOUN
fcis-7982	34	19	space	space	NOUN
fcis-7982	34	20	contains	contain	VERB
fcis-7982	34	21	the	the	DET
fcis-7982	34	22	optimal	optimal	ADJ
fcis-7982	34	23	architectures	architecture	NOUN
fcis-7982	34	24	,	,	PUNCT
fcis-7982	34	25	but	but	CCONJ
fcis-7982	34	26	when	when	SCONJ
fcis-7982	34	27	the	the	DET
fcis-7982	34	28	search	search	NOUN
fcis-7982	34	29	space	space	NOUN
fcis-7982	34	30	is	be	AUX
fcis-7982	34	31	too	too	ADV
fcis-7982	34	32	large	large	ADJ
fcis-7982	34	33	,	,	PUNCT
fcis-7982	34	34	the	the	DET
fcis-7982	34	35	search	search	NOUN
fcis-7982	34	36	process	process	NOUN
fcis-7982	34	37	consumes	consume	VERB
fcis-7982	34	38	a	a	DET
fcis-7982	34	39	lot	lot	NOUN
fcis-7982	34	40	of	of	ADP
fcis-7982	34	41	time	time	NOUN
fcis-7982	34	42	and	and	CCONJ
fcis-7982	34	43	computational	computational	ADJ
fcis-7982	34	44	resources	resource	NOUN
fcis-7982	34	45	,	,	PUNCT
fcis-7982	34	46	and	and	CCONJ
fcis-7982	34	47	it	it	PRON
fcis-7982	34	48	is	be	AUX
fcis-7982	34	49	difficult	difficult	ADJ
fcis-7982	34	50	to	to	PART
fcis-7982	34	51	find	find	VERB
fcis-7982	34	52	the	the	DET
fcis-7982	34	53	optimal	optimal	ADJ
fcis-7982	34	54	architectures	architecture	NOUN
fcis-7982	34	55	.	.	PUNCT
fcis-7982	35	1	therefore	therefore	ADV
fcis-7982	35	2	,	,	PUNCT
fcis-7982	35	3	researchers	researcher	NOUN
fcis-7982	35	4	generally	generally	ADV
fcis-7982	35	5	tailor	tailor	VERB
fcis-7982	35	6	specific	specific	ADJ
fcis-7982	35	7	search	search	NOUN
fcis-7982	35	8	spaces	space	NOUN
fcis-7982	35	9	for	for	ADP
fcis-7982	35	10	specific	specific	ADJ
fcis-7982	35	11	tasks	task	NOUN
fcis-7982	35	12	to	to	PART
fcis-7982	35	13	improve	improve	VERB
fcis-7982	35	14	the	the	DET
fcis-7982	35	15	search	search	NOUN
fcis-7982	35	16	space	space	NOUN
fcis-7982	35	17	according	accord	VERB
fcis-7982	35	18	to	to	ADP
fcis-7982	35	19	the	the	DET
fcis-7982	35	20	characteristics	characteristic	NOUN
fcis-7982	35	21	of	of	ADP
fcis-7982	35	22	the	the	DET
fcis-7982	35	23	tasks	task	NOUN
fcis-7982	35	24	to	to	PART
fcis-7982	35	25	be	be	AUX
fcis-7982	35	26	solved	solve	VERB
fcis-7982	35	27	.	.	PUNCT
fcis-7982	36	1	the	the	DET
fcis-7982	36	2	search	search	NOUN
fcis-7982	36	3	strategy	strategy	NOUN
fcis-7982	36	4	and	and	CCONJ
fcis-7982	36	5	performance	performance	NOUN
fcis-7982	36	6	evaluation	evaluation	NOUN
fcis-7982	36	7	strategy	strategy	NOUN
fcis-7982	36	8	are	be	AUX
fcis-7982	36	9	often	often	ADV
fcis-7982	36	10	closely	closely	ADV
fcis-7982	36	11	related	relate	VERB
fcis-7982	36	12	,	,	PUNCT
fcis-7982	36	13	with	with	ADP
fcis-7982	36	14	the	the	DET
fcis-7982	36	15	search	search	NOUN
fcis-7982	36	16	strategy	strategy	NOUN
fcis-7982	36	17	describing	describe	VERB
fcis-7982	36	18	the	the	DET
fcis-7982	36	19	way	way	NOUN
fcis-7982	36	20	we	we	PRON
fcis-7982	36	21	search	search	VERB
fcis-7982	36	22	the	the	DET
fcis-7982	36	23	search	search	NOUN
fcis-7982	36	24	space	space	NOUN
fcis-7982	36	25	and	and	CCONJ
fcis-7982	36	26	the	the	DET
fcis-7982	36	27	performance	performance	NOUN
fcis-7982	36	28	evaluation	evaluation	NOUN
fcis-7982	36	29	strategy	strategy	NOUN
fcis-7982	36	30	describing	describe	VERB
fcis-7982	36	31	the	the	DET
fcis-7982	36	32	way	way	NOUN
fcis-7982	36	33	we	we	PRON
fcis-7982	36	34	evaluate	evaluate	VERB
fcis-7982	36	35	the	the	DET
fcis-7982	36	36	performance	performance	NOUN
fcis-7982	36	37	of	of	ADP
fcis-7982	36	38	the	the	DET
fcis-7982	36	39	searched	search	VERB
fcis-7982	36	40	architecture	architecture	NOUN
fcis-7982	36	41	and	and	CCONJ
fcis-7982	36	42	guide	guide	VERB
fcis-7982	36	43	the	the	DET
fcis-7982	36	44	next	next	ADJ
fcis-7982	36	45	architecture	architecture	NOUN
fcis-7982	36	46	search	search	NOUN
fcis-7982	36	47	process	process	NOUN
fcis-7982	36	48	.	.	PUNCT
fcis-7982	37	1	currently	currently	ADV
fcis-7982	37	2	,	,	PUNCT
fcis-7982	37	3	there	there	PRON
fcis-7982	37	4	are	be	VERB
fcis-7982	37	5	two	two	NUM
fcis-7982	37	6	main	main	ADJ
fcis-7982	37	7	mainstream	mainstream	NOUN
fcis-7982	37	8	approaches	approach	NOUN
fcis-7982	37	9	for	for	ADP
fcis-7982	37	10	nas	nas	PROPN
fcis-7982	37	11	,	,	PUNCT
fcis-7982	37	12	a	a	DET
fcis-7982	37	13	stand	stand	VERB
fcis-7982	37	14	-	-	PUNCT
fcis-7982	37	15	alone	alone	ADV
fcis-7982	37	16	evaluation	evaluation	NOUN
fcis-7982	37	17	strategy	strategy	NOUN
fcis-7982	37	18	(	(	PUNCT
fcis-7982	37	19	stand	stand	VERB
fcis-7982	37	20	-	-	PUNCT
fcis-7982	37	21	alone	alone	ADV
fcis-7982	37	22	method	method	NOUN
fcis-7982	37	23	)	)	PUNCT
fcis-7982	37	24	and	and	CCONJ
fcis-7982	37	25	a	a	DET
fcis-7982	37	26	one	one	NUM
fcis-7982	37	27	-	-	PUNCT
fcis-7982	37	28	time	time	NOUN
fcis-7982	37	29	evaluation	evaluation	NOUN
fcis-7982	37	30	strategy	strategy	NOUN
fcis-7982	38	1	[	[	X
fcis-7982	38	2	3	3	X
fcis-7982	38	3	]	]	X
fcis-7982	38	4	(	(	PUNCT
fcis-7982	38	5	one	one	NUM
fcis-7982	38	6	-	-	PUNCT
fcis-7982	38	7	shot	shot	NOUN
fcis-7982	38	8	method	method	NOUN
fcis-7982	38	9	)	)	PUNCT
fcis-7982	38	10	.	.	PUNCT
fcis-7982	39	1	the	the	DET
fcis-7982	39	2	difference	difference	NOUN
fcis-7982	39	3	between	between	ADP
fcis-7982	39	4	them	they	PRON
fcis-7982	39	5	mainly	mainly	ADV
fcis-7982	39	6	lies	lie	VERB
fcis-7982	39	7	in	in	ADP
fcis-7982	39	8	whether	whether	SCONJ
fcis-7982	39	9	the	the	DET
fcis-7982	39	10	architectural	architectural	ADJ
fcis-7982	39	11	parameters	parameter	NOUN
fcis-7982	39	12	are	be	AUX
fcis-7982	39	13	shared	share	VERB
fcis-7982	39	14	among	among	ADP
fcis-7982	39	15	different	different	ADJ
fcis-7982	39	16	architectures	architecture	NOUN
fcis-7982	39	17	in	in	ADP
fcis-7982	39	18	the	the	DET
fcis-7982	39	19	search	search	NOUN
fcis-7982	39	20	space	space	NOUN
fcis-7982	39	21	.	.	PUNCT
fcis-7982	40	1	the	the	DET
fcis-7982	40	2	independent	independent	ADJ
fcis-7982	40	3	evaluation	evaluation	NOUN
fcis-7982	40	4	strategy	strategy	NOUN
fcis-7982	40	5	starts	start	VERB
fcis-7982	40	6	from	from	ADP
fcis-7982	40	7	the	the	DET
fcis-7982	40	8	initial	initial	ADJ
fcis-7982	40	9	state	state	NOUN
fcis-7982	40	10	to	to	PART
fcis-7982	40	11	train	train	VERB
fcis-7982	40	12	and	and	CCONJ
fcis-7982	40	13	evaluate	evaluate	VERB
fcis-7982	40	14	each	each	DET
fcis-7982	40	15	model	model	NOUN
fcis-7982	40	16	,	,	PUNCT
fcis-7982	40	17	which	which	PRON
fcis-7982	40	18	is	be	AUX
fcis-7982	40	19	a	a	DET
fcis-7982	40	20	more	more	ADV
fcis-7982	40	21	reliable	reliable	ADJ
fcis-7982	40	22	evaluation	evaluation	NOUN
fcis-7982	40	23	method	method	NOUN
fcis-7982	40	24	because	because	SCONJ
fcis-7982	40	25	of	of	ADP
fcis-7982	40	26	the	the	DET
fcis-7982	40	27	accurate	accurate	ADJ
fcis-7982	40	28	evaluation	evaluation	NOUN
fcis-7982	40	29	results	result	NOUN
fcis-7982	40	30	.	.	PUNCT
fcis-7982	41	1	the	the	DET
fcis-7982	41	2	core	core	ADJ
fcis-7982	41	3	idea	idea	NOUN
fcis-7982	41	4	of	of	ADP
fcis-7982	41	5	one	one	NUM
fcis-7982	41	6	-	-	PUNCT
fcis-7982	41	7	time	time	NOUN
fcis-7982	41	8	evaluation	evaluation	NOUN
fcis-7982	41	9	lies	lie	VERB
fcis-7982	41	10	in	in	ADP
fcis-7982	41	11	parameter	parameter	NOUN
fcis-7982	41	12	share	share	NOUN
fcis-7982	41	13	,	,	PUNCT
fcis-7982	41	14	which	which	PRON
fcis-7982	41	15	treats	treat	VERB
fcis-7982	41	16	the	the	DET
fcis-7982	41	17	search	search	NOUN
fcis-7982	41	18	space	space	NOUN
fcis-7982	41	19	as	as	ADP
fcis-7982	41	20	a	a	DET
fcis-7982	41	21	supernet	supernet	NOUN
fcis-7982	41	22	,	,	PUNCT
fcis-7982	41	23	and	and	CCONJ
fcis-7982	41	24	different	different	ADJ
fcis-7982	41	25	neural	neural	ADJ
fcis-7982	41	26	networks	network	NOUN
fcis-7982	41	27	as	as	ADP
fcis-7982	41	28	subnets	subnet	NOUN
fcis-7982	41	29	on	on	ADP
fcis-7982	41	30	the	the	DET
fcis-7982	41	31	supernet	supernet	NOUN
fcis-7982	41	32	,	,	PUNCT
fcis-7982	41	33	and	and	CCONJ
fcis-7982	41	34	different	different	ADJ
fcis-7982	41	35	subnets	subnet	NOUN
fcis-7982	41	36	share	share	VERB
fcis-7982	41	37	the	the	DET
fcis-7982	41	38	parameters	parameter	NOUN
fcis-7982	41	39	of	of	ADP
fcis-7982	41	40	the	the	DET
fcis-7982	41	41	supernet	supernet	NOUN
fcis-7982	41	42	,	,	PUNCT
fcis-7982	41	43	this	this	DET
fcis-7982	41	44	method	method	NOUN
fcis-7982	41	45	avoids	avoid	VERB
fcis-7982	41	46	training	train	VERB
fcis-7982	41	47	each	each	DET
fcis-7982	41	48	model	model	NOUN
fcis-7982	41	49	from	from	ADP
fcis-7982	41	50	scratch	scratch	NOUN
fcis-7982	41	51	and	and	CCONJ
fcis-7982	41	52	is	be	AUX
fcis-7982	41	53	more	more	ADV
fcis-7982	41	54	efficient	efficient	ADJ
fcis-7982	41	55	,	,	PUNCT
fcis-7982	41	56	but	but	CCONJ
fcis-7982	41	57	the	the	DET
fcis-7982	41	58	accuracy	accuracy	NOUN
fcis-7982	41	59	of	of	ADP
fcis-7982	41	60	evaluation	evaluation	NOUN
fcis-7982	41	61	decreases	decrease	NOUN
fcis-7982	41	62	as	as	ADP
fcis-7982	41	63	the	the	DET
fcis-7982	41	64	search	search	NOUN
fcis-7982	41	65	space	space	NOUN
fcis-7982	41	66	increases	increase	NOUN
fcis-7982	41	67	,	,	PUNCT
fcis-7982	41	68	therefore	therefore	ADV
fcis-7982	41	69	,	,	PUNCT
fcis-7982	41	70	the	the	DET
fcis-7982	41	71	one	one	NUM
fcis-7982	41	72	-	-	PUNCT
fcis-7982	41	73	time	time	NOUN
fcis-7982	41	74	evaluation	evaluation	NOUN
fcis-7982	41	75	strategy	strategy	NOUN
fcis-7982	41	76	is	be	AUX
fcis-7982	41	77	mostly	mostly	ADV
fcis-7982	41	78	used	use	VERB
fcis-7982	41	79	on	on	ADP
fcis-7982	41	80	small	small	ADJ
fcis-7982	41	81	search	search	NOUN
fcis-7982	41	82	spaces	space	NOUN
fcis-7982	41	83	.	.	PUNCT
fcis-7982	42	1	3	3	X
fcis-7982	42	2	.	.	X
fcis-7982	42	3	introduction	introduction	NOUN
fcis-7982	42	4	of	of	ADP
fcis-7982	42	5	preliminary	preliminary	ADJ
fcis-7982	42	6	algorithms	algorithm	NOUN
fcis-7982	42	7	the	the	DET
fcis-7982	42	8	networks	network	NOUN
fcis-7982	42	9	commonly	commonly	ADV
fcis-7982	42	10	used	use	VERB
fcis-7982	42	11	to	to	PART
fcis-7982	42	12	solve	solve	VERB
fcis-7982	42	13	the	the	DET
fcis-7982	42	14	knowledge	knowledge	NOUN
fcis-7982	42	15	graph	graph	NOUN
fcis-7982	42	16	embedding	embed	VERB
fcis-7982	42	17	problem	problem	NOUN
fcis-7982	42	18	are	be	AUX
fcis-7982	42	19	graph	graph	VERB
fcis-7982	42	20	neural	neural	ADJ
fcis-7982	42	21	network	network	NOUN
fcis-7982	42	22	(	(	PUNCT
fcis-7982	42	23	gnn	gnn	PROPN
fcis-7982	42	24	)	)	PUNCT
fcis-7982	42	25	and	and	CCONJ
fcis-7982	42	26	recurrent	recurrent	ADJ
fcis-7982	42	27	neural	neural	ADJ
fcis-7982	42	28	network	network	NOUN
fcis-7982	42	29	(	(	PUNCT
fcis-7982	42	30	rnn	rnn	PROPN
fcis-7982	42	31	)	)	PUNCT
fcis-7982	43	1	[	[	X
fcis-7982	43	2	4	4	NUM
fcis-7982	43	3	]	]	PUNCT
fcis-7982	43	4	.	.	PUNCT
fcis-7982	44	1	here	here	ADV
fcis-7982	44	2	we	we	PRON
fcis-7982	44	3	use	use	VERB
fcis-7982	44	4	recurrent	recurrent	ADJ
fcis-7982	44	5	neural	neural	ADJ
fcis-7982	44	6	network	network	NOUN
fcis-7982	44	7	,	,	PUNCT
fcis-7982	44	8	which	which	PRON
fcis-7982	44	9	is	be	AUX
fcis-7982	44	10	good	good	ADJ
fcis-7982	44	11	at	at	ADP
fcis-7982	44	12	processing	process	VERB
fcis-7982	44	13	sequential	sequential	ADJ
fcis-7982	44	14	data	datum	NOUN
fcis-7982	44	15	,	,	PUNCT
fcis-7982	44	16	as	as	ADP
fcis-7982	44	17	the	the	DET
fcis-7982	44	18	target	target	NOUN
fcis-7982	44	19	architecture	architecture	NOUN
fcis-7982	44	20	.	.	PUNCT
fcis-7982	45	1	in	in	ADP
fcis-7982	45	2	this	this	DET
fcis-7982	45	3	problem	problem	NOUN
fcis-7982	45	4	,	,	PUNCT
fcis-7982	45	5	the	the	DET
fcis-7982	45	6	recurrent	recurrent	ADJ
fcis-7982	45	7	neural	neural	ADJ
fcis-7982	45	8	network	network	NOUN
fcis-7982	45	9	obtains	obtain	VERB
fcis-7982	45	10	the	the	DET
fcis-7982	45	11	embedding	embedding	NOUN
fcis-7982	45	12	of	of	ADP
fcis-7982	45	13	𝑠1	𝑠1	PROPN
fcis-7982	45	14	,	,	PUNCT
fcis-7982	45	15	𝑟1	𝑟1	NOUN
fcis-7982	45	16	by	by	ADP
fcis-7982	45	17	iteratively	iteratively	ADV
fcis-7982	45	18	processing	process	VERB
fcis-7982	45	19	𝑠𝐿	𝑠𝐿	PROPN
fcis-7982	45	20	,	,	PUNCT
fcis-7982	45	21	𝑟𝐿.	𝑟𝐿.	VERB
fcis-7982	45	22	the	the	DET
fcis-7982	45	23	input	input	NOUN
fcis-7982	45	24	of	of	ADP
fcis-7982	45	25	the	the	DET
fcis-7982	45	26	architecture	architecture	NOUN
fcis-7982	45	27	at	at	ADP
fcis-7982	45	28	each	each	DET
fcis-7982	45	29	step	step	NOUN
fcis-7982	45	30	t	t	NOUN
fcis-7982	45	31	is	be	AUX
fcis-7982	45	32	𝑠𝑡,𝑟𝑡	𝑠𝑡,𝑟𝑡	NOUN
fcis-7982	45	33	,	,	PUNCT
fcis-7982	45	34	ℎ𝑡−1	ℎ𝑡−1	ADJ
fcis-7982	45	35	,	,	PUNCT
fcis-7982	45	36	and	and	CCONJ
fcis-7982	45	37	the	the	DET
fcis-7982	45	38	output	output	NOUN
fcis-7982	45	39	is	be	AUX
fcis-7982	45	40	𝑣𝑡,ℎ𝑡.	𝑣𝑡,ℎ𝑡.	NOUN
fcis-7982	45	41	the	the	DET
fcis-7982	45	42	whole	whole	ADJ
fcis-7982	45	43	architecture	architecture	NOUN
fcis-7982	45	44	can	can	AUX
fcis-7982	45	45	be	be	AUX
fcis-7982	45	46	defined	define	VERB
fcis-7982	45	47	as	as	ADP
fcis-7982	45	48	the	the	DET
fcis-7982	45	49	following	follow	VERB
fcis-7982	45	50	recursive	recursive	ADJ
fcis-7982	45	51	function	function	NOUN
fcis-7982	45	52	.	.	PUNCT
fcis-7982	46	1	[	[	X
fcis-7982	46	2	𝑣𝑡	𝑣𝑡	NOUN
fcis-7982	46	3	,	,	PUNCT
fcis-7982	46	4	ℎ𝑡	ℎ𝑡	NOUN
fcis-7982	46	5	]	]	PUNCT
fcis-7982	46	6	=	=	SYM
fcis-7982	46	7	𝑓(𝑠𝑡	𝑓(𝑠𝑡	NOUN
fcis-7982	46	8	,	,	PUNCT
fcis-7982	46	9	𝑟𝑡	𝑟𝑡	PROPN
fcis-7982	46	10	,	,	PUNCT
fcis-7982	46	11	ℎ𝑡−1	ℎ𝑡−1	PROPN
fcis-7982	46	12	)	)	PUNCT
fcis-7982	46	13	,	,	PUNCT
fcis-7982	46	14	∀𝑡	∀𝑡	PUNCT
fcis-7982	46	15	=	=	SYM
fcis-7982	46	16	1	1	NUM
fcis-7982	46	17	…	…	SYM
fcis-7982	46	18	𝐿	𝐿	PROPN
fcis-7982	46	19	(	(	PUNCT
fcis-7982	46	20	1	1	NUM
fcis-7982	46	21	)	)	PUNCT
fcis-7982	46	22	where	where	SCONJ
fcis-7982	46	23	,	,	PUNCT
fcis-7982	46	24	ℎ𝑡	ℎ𝑡	NOUN
fcis-7982	46	25	is	be	AUX
fcis-7982	46	26	the	the	DET
fcis-7982	46	27	implicit	implicit	ADJ
fcis-7982	46	28	state	state	NOUN
fcis-7982	46	29	in	in	ADP
fcis-7982	46	30	the	the	DET
fcis-7982	46	31	architecture	architecture	NOUN
fcis-7982	46	32	,	,	PUNCT
fcis-7982	46	33	initially	initially	ADV
fcis-7982	46	34	ℎ0	ℎ0	PROPN
fcis-7982	46	35	=	=	PROPN
fcis-7982	46	36	𝑠1	𝑠1	PROPN
fcis-7982	46	37	.	.	PUNCT
fcis-7982	47	1	the	the	DET
fcis-7982	47	2	output	output	NOUN
fcis-7982	47	3	𝑣𝑡	𝑣𝑡	ADP
fcis-7982	47	4	is	be	AUX
fcis-7982	47	5	used	use	VERB
fcis-7982	47	6	to	to	PART
fcis-7982	47	7	predict	predict	VERB
fcis-7982	47	8	the	the	DET
fcis-7982	47	9	tail	tail	NOUN
fcis-7982	47	10	entity	entity	NOUN
fcis-7982	47	11	𝑜𝑡.	𝑜𝑡.	VERB
fcis-7982	47	12	in	in	ADP
fcis-7982	47	13	the	the	DET
fcis-7982	47	14	search	search	NOUN
fcis-7982	47	15	process	process	NOUN
fcis-7982	47	16	,	,	PUNCT
fcis-7982	47	17	if	if	SCONJ
fcis-7982	47	18	all	all	DET
fcis-7982	47	19	the	the	DET
fcis-7982	47	20	parameters	parameter	NOUN
fcis-7982	47	21	to	to	PART
fcis-7982	47	22	be	be	AUX
fcis-7982	47	23	searched	search	VERB
fcis-7982	47	24	are	be	AUX
fcis-7982	47	25	put	put	VERB
fcis-7982	47	26	into	into	ADP
fcis-7982	47	27	one	one	NUM
fcis-7982	47	28	search	search	NOUN
fcis-7982	47	29	space	space	NOUN
fcis-7982	47	30	,	,	PUNCT
fcis-7982	47	31	the	the	DET
fcis-7982	47	32	search	search	NOUN
fcis-7982	47	33	space	space	NOUN
fcis-7982	47	34	will	will	AUX
fcis-7982	47	35	be	be	AUX
fcis-7982	47	36	quite	quite	ADV
fcis-7982	47	37	huge	huge	ADJ
fcis-7982	47	38	.	.	PUNCT
fcis-7982	48	1	if	if	SCONJ
fcis-7982	48	2	a	a	DET
fcis-7982	48	3	stand	stand	VERB
fcis-7982	48	4	-	-	PUNCT
fcis-7982	48	5	alone	alone	ADJ
fcis-7982	48	6	evaluation	evaluation	NOUN
fcis-7982	48	7	method	method	NOUN
fcis-7982	48	8	is	be	AUX
fcis-7982	48	9	used	use	VERB
fcis-7982	48	10	to	to	PART
fcis-7982	48	11	evaluate	evaluate	VERB
fcis-7982	48	12	the	the	DET
fcis-7982	48	13	architecture	architecture	NOUN
fcis-7982	48	14	,	,	PUNCT
fcis-7982	48	15	it	it	PRON
fcis-7982	48	16	will	will	AUX
fcis-7982	48	17	give	give	VERB
fcis-7982	48	18	accurate	accurate	ADJ
fcis-7982	48	19	feedback	feedback	NOUN
fcis-7982	48	20	on	on	ADP
fcis-7982	48	21	the	the	DET
fcis-7982	48	22	performance	performance	NOUN
fcis-7982	48	23	of	of	ADP
fcis-7982	48	24	the	the	DET
fcis-7982	48	25	architecture	architecture	NOUN
fcis-7982	48	26	,	,	PUNCT
fcis-7982	48	27	but	but	CCONJ
fcis-7982	48	28	it	it	PRON
fcis-7982	48	29	will	will	AUX
fcis-7982	48	30	take	take	VERB
fcis-7982	48	31	a	a	DET
fcis-7982	48	32	long	long	ADJ
fcis-7982	48	33	time	time	NOUN
fcis-7982	48	34	and	and	CCONJ
fcis-7982	48	35	consume	consume	VERB
fcis-7982	48	36	huge	huge	ADJ
fcis-7982	48	37	resources	resource	NOUN
fcis-7982	48	38	[	[	X
fcis-7982	48	39	5	5	NUM
fcis-7982	48	40	]	]	PUNCT
fcis-7982	48	41	.	.	PUNCT
fcis-7982	49	1	if	if	SCONJ
fcis-7982	49	2	a	a	DET
fcis-7982	49	3	one	one	NUM
fcis-7982	49	4	-	-	PUNCT
fcis-7982	49	5	time	time	NOUN
fcis-7982	49	6	evaluation	evaluation	NOUN
fcis-7982	49	7	method	method	NOUN
fcis-7982	49	8	is	be	AUX
fcis-7982	49	9	used	use	VERB
fcis-7982	49	10	to	to	PART
fcis-7982	49	11	evaluate	evaluate	VERB
fcis-7982	49	12	the	the	DET
fcis-7982	49	13	architectures	architecture	NOUN
fcis-7982	49	14	,	,	PUNCT
fcis-7982	49	15	an	an	DET
fcis-7982	49	16	accurate	accurate	ADJ
fcis-7982	49	17	performance	performance	NOUN
fcis-7982	49	18	evaluation	evaluation	NOUN
fcis-7982	49	19	of	of	ADP
fcis-7982	49	20	the	the	DET
fcis-7982	49	21	candidate	candidate	NOUN
fcis-7982	49	22	architectures	architecture	NOUN
fcis-7982	49	23	can	can	AUX
fcis-7982	49	24	not	not	PART
fcis-7982	49	25	be	be	AUX
fcis-7982	49	26	obtained	obtain	VERB
fcis-7982	49	27	because	because	SCONJ
fcis-7982	49	28	of	of	ADP
fcis-7982	49	29	the	the	DET
fcis-7982	49	30	huge	huge	ADJ
fcis-7982	49	31	search	search	NOUN
fcis-7982	49	32	space.the	space.the	DET
fcis-7982	49	33	interstellar	interstellar	ADJ
fcis-7982	49	34	algorithm	algorithm	NOUN
fcis-7982	49	35	[	[	X
fcis-7982	49	36	6	6	NUM
fcis-7982	49	37	]	]	PUNCT
fcis-7982	49	38	proposes	propose	VERB
fcis-7982	49	39	to	to	PART
fcis-7982	49	40	define	define	VERB
fcis-7982	49	41	all	all	DET
fcis-7982	49	42	possible	possible	ADJ
fcis-7982	49	43	architectures	architecture	NOUN
fcis-7982	49	44	as	as	ADP
fcis-7982	49	45	a	a	DET
fcis-7982	49	46	search	search	NOUN
fcis-7982	49	47	space	space	NOUN
fcis-7982	49	48	and	and	CCONJ
fcis-7982	49	49	divide	divide	VERB
fcis-7982	49	50	the	the	DET
fcis-7982	49	51	entire	entire	ADJ
fcis-7982	49	52	search	search	NOUN
fcis-7982	49	53	space	space	NOUN
fcis-7982	49	54	into	into	ADP
fcis-7982	49	55	a	a	DET
fcis-7982	49	56	macroscopic	macroscopic	ADJ
fcis-7982	49	57	search	search	NOUN
fcis-7982	49	58	space	space	NOUN
fcis-7982	49	59	and	and	CCONJ
fcis-7982	49	60	a	a	DET
fcis-7982	49	61	microscopic	microscopic	ADJ
fcis-7982	49	62	search	search	NOUN
fcis-7982	49	63	space	space	NOUN
fcis-7982	49	64	according	accord	VERB
fcis-7982	49	65	to	to	ADP
fcis-7982	49	66	the	the	DET
fcis-7982	49	67	degree	degree	NOUN
fcis-7982	49	68	of	of	ADP
fcis-7982	49	69	impact	impact	NOUN
fcis-7982	49	70	on	on	ADP
fcis-7982	49	71	information	information	NOUN
fcis-7982	49	72	flow	flow	NOUN
fcis-7982	49	73	.	.	PUNCT
fcis-7982	50	1	the	the	DET
fcis-7982	50	2	results	result	NOUN
fcis-7982	50	3	of	of	ADP
fcis-7982	50	4	the	the	DET
fcis-7982	50	5	delineation	delineation	NOUN
fcis-7982	50	6	are	be	AUX
fcis-7982	50	7	shown	show	VERB
fcis-7982	50	8	in	in	ADP
fcis-7982	50	9	the	the	DET
fcis-7982	50	10	following	follow	VERB
fcis-7982	50	11	table	table	NOUN
fcis-7982	50	12	1	1	NUM
fcis-7982	50	13	.	.	PUNCT
fcis-7982	51	1	there	there	PRON
fcis-7982	51	2	are	be	VERB
fcis-7982	51	3	about	about	ADP
fcis-7982	51	4	candidate	candidate	NOUN
fcis-7982	51	5	architectures	architecture	NOUN
fcis-7982	51	6	in	in	ADP
fcis-7982	51	7	the	the	DET
fcis-7982	51	8	search	search	NOUN
fcis-7982	51	9	space	space	NOUN
fcis-7982	51	10	before	before	ADP
fcis-7982	51	11	the	the	DET
fcis-7982	51	12	search	search	NOUN
fcis-7982	51	13	space	space	NOUN
fcis-7982	51	14	partition	partition	NOUN
fcis-7982	51	15	,	,	PUNCT
fcis-7982	51	16	which	which	PRON
fcis-7982	51	17	is	be	AUX
fcis-7982	51	18	quite	quite	ADV
fcis-7982	51	19	large	large	ADJ
fcis-7982	51	20	and	and	CCONJ
fcis-7982	51	21	the	the	DET
fcis-7982	51	22	search	search	NOUN
fcis-7982	51	23	process	process	NOUN
fcis-7982	51	24	is	be	AUX
fcis-7982	51	25	extremely	extremely	ADV
fcis-7982	51	26	computationally	computationally	ADV
fcis-7982	51	27	intensive	intensive	ADJ
fcis-7982	51	28	.	.	PUNCT
fcis-7982	52	1	there	there	PRON
fcis-7982	52	2	are	be	VERB
fcis-7982	52	3	architectures	architecture	NOUN
fcis-7982	52	4	in	in	ADP
fcis-7982	52	5	the	the	DET
fcis-7982	52	6	macro	macro	ADJ
fcis-7982	52	7	space	space	NOUN
fcis-7982	52	8	and	and	CCONJ
fcis-7982	52	9	architectures	architecture	NOUN
fcis-7982	52	10	in	in	ADP
fcis-7982	52	11	the	the	DET
fcis-7982	52	12	micro	micro	ADJ
fcis-7982	52	13	space	space	NOUN
fcis-7982	52	14	after	after	ADP
fcis-7982	52	15	the	the	DET
fcis-7982	52	16	partition	partition	NOUN
fcis-7982	52	17	.	.	PUNCT
fcis-7982	53	1	it	it	PRON
fcis-7982	53	2	can	can	AUX
fcis-7982	53	3	be	be	AUX
fcis-7982	53	4	seen	see	VERB
fcis-7982	53	5	that	that	SCONJ
fcis-7982	53	6	after	after	ADP
fcis-7982	53	7	the	the	DET
fcis-7982	53	8	partitioning	partitioning	NOUN
fcis-7982	53	9	,	,	PUNCT
fcis-7982	53	10	both	both	CCONJ
fcis-7982	53	11	the	the	DET
fcis-7982	53	12	macroscopic	macroscopic	ADJ
fcis-7982	53	13	space	space	NOUN
fcis-7982	53	14	and	and	CCONJ
fcis-7982	53	15	the	the	DET
fcis-7982	53	16	microscopic	microscopic	ADJ
fcis-7982	53	17	space	space	NOUN
fcis-7982	53	18	achieve	achieve	VERB
fcis-7982	53	19	an	an	DET
fcis-7982	53	20	exponential	exponential	ADJ
fcis-7982	53	21	decrease	decrease	NOUN
fcis-7982	53	22	in	in	ADP
fcis-7982	53	23	size	size	NOUN
fcis-7982	53	24	compared	compare	VERB
fcis-7982	53	25	with	with	ADP
fcis-7982	53	26	the	the	DET
fcis-7982	53	27	space	space	NOUN
fcis-7982	53	28	before	before	ADP
fcis-7982	53	29	the	the	DET
fcis-7982	53	30	partitioning	partitioning	NOUN
fcis-7982	53	31	.	.	PUNCT
fcis-7982	54	1	the	the	DET
fcis-7982	54	2	macroscopic	macroscopic	ADJ
fcis-7982	54	3	search	search	NOUN
fcis-7982	54	4	space	space	NOUN
fcis-7982	54	5	is	be	AUX
fcis-7982	54	6	larger	large	ADJ
fcis-7982	54	7	and	and	CCONJ
fcis-7982	54	8	uses	use	VERB
fcis-7982	54	9	an	an	DET
fcis-7982	54	10	independent	independent	ADJ
fcis-7982	54	11	evaluation	evaluation	NOUN
fcis-7982	54	12	strategy	strategy	NOUN
fcis-7982	54	13	,	,	PUNCT
fcis-7982	54	14	while	while	SCONJ
fcis-7982	54	15	the	the	DET
fcis-7982	54	16	microscopic	microscopic	ADJ
fcis-7982	54	17	space	space	NOUN
fcis-7982	54	18	is	be	AUX
fcis-7982	54	19	smaller	small	ADJ
fcis-7982	54	20	and	and	CCONJ
fcis-7982	54	21	uses	use	VERB
fcis-7982	54	22	a	a	DET
fcis-7982	54	23	one	one	NUM
fcis-7982	54	24	-	-	PUNCT
fcis-7982	54	25	time	time	NOUN
fcis-7982	54	26	evaluation	evaluation	NOUN
fcis-7982	54	27	strategy	strategy	NOUN
fcis-7982	54	28	.	.	PUNCT
fcis-7982	55	1	table	table	NOUN
fcis-7982	55	2	1	1	NUM
fcis-7982	55	3	.	.	PUNCT
fcis-7982	55	4	description	description	NOUN
fcis-7982	55	5	of	of	ADP
fcis-7982	55	6	macrospace	macrospace	NOUN
fcis-7982	55	7	and	and	CCONJ
fcis-7982	55	8	microspace	microspace	NOUN
fcis-7982	55	9	division	division	NOUN
fcis-7982	55	10	macro	macro	ADJ
fcis-7982	55	11	-	-	NOUN
fcis-7982	55	12	level	level	ADJ
fcis-7982	55	13	micro	micro	ADJ
fcis-7982	55	14	-	-	NOUN
fcis-7982	55	15	level	level	ADJ
fcis-7982	55	16	connections	connection	NOUN
fcis-7982	55	17	combinators	combinator	VERB
fcis-7982	55	18	activation	activation	NOUN
fcis-7982	55	19	weight	weight	NOUN
fcis-7982	55	20	matrix	matrix	NOUN
fcis-7982	55	21	ℎ𝑡−1	ℎ𝑡−1	NOUN
fcis-7982	55	22	,	,	PUNCT
fcis-7982	55	23	𝑂𝑠	𝑂𝑠	PROPN
fcis-7982	55	24	,	,	PUNCT
fcis-7982	55	25	0	0	NUM
fcis-7982	55	26	,	,	PUNCT
fcis-7982	55	27	𝑠𝑡	𝑠𝑡	PROPN
fcis-7982	55	28	+	+	PROPN
fcis-7982	55	29	,	,	PUNCT
fcis-7982	55	30	,,gated	,,gated	ADJ
fcis-7982	55	31	identity	identity	NOUN
fcis-7982	55	32	,	,	PUNCT
fcis-7982	55	33	tanh	tanh	NOUN
fcis-7982	55	34	,	,	PUNCT
fcis-7982	55	35	sigmoid	sigmoid	NOUN
fcis-7982	55	36	{	{	PUNCT
fcis-7982	55	37	𝑊𝑖}𝑖=1	𝑊𝑖}𝑖=1	NOUN
fcis-7982	55	38	6	6	NUM
fcis-7982	55	39	.	.	PUNCT
fcis-7982	56	1	𝐼	𝐼	ADP
fcis-7982	56	2	4	4	NUM
fcis-7982	56	3	.	.	PUNCT
fcis-7982	56	4	algorithm	algorithm	NOUN
fcis-7982	56	5	introduction	introduction	NOUN
fcis-7982	56	6	the	the	DET
fcis-7982	56	7	current	current	ADJ
fcis-7982	56	8	mainstream	mainstream	NOUN
fcis-7982	56	9	evaluation	evaluation	NOUN
fcis-7982	56	10	methods	method	NOUN
fcis-7982	56	11	for	for	ADP
fcis-7982	56	12	neural	neural	ADJ
fcis-7982	56	13	network	network	NOUN
fcis-7982	56	14	architectures	architecture	NOUN
fcis-7982	56	15	are	be	AUX
fcis-7982	56	16	independent	independent	ADJ
fcis-7982	56	17	evaluation	evaluation	NOUN
fcis-7982	56	18	methods	method	NOUN
fcis-7982	56	19	and	and	CCONJ
fcis-7982	56	20	one	one	NUM
fcis-7982	56	21	-	-	PUNCT
fcis-7982	56	22	time	time	NOUN
fcis-7982	56	23	evaluation	evaluation	NOUN
fcis-7982	56	24	methods	method	NOUN
fcis-7982	56	25	.	.	PUNCT
fcis-7982	57	1	the	the	DET
fcis-7982	57	2	independent	independent	ADJ
fcis-7982	57	3	evaluation	evaluation	NOUN
fcis-7982	57	4	methods	method	NOUN
fcis-7982	57	5	start	start	VERB
fcis-7982	57	6	from	from	ADP
fcis-7982	57	7	initialization	initialization	NOUN
fcis-7982	57	8	to	to	PART
fcis-7982	57	9	train	train	VERB
fcis-7982	57	10	each	each	DET
fcis-7982	57	11	subnet	subnet	NOUN
fcis-7982	57	12	and	and	CCONJ
fcis-7982	57	13	get	get	VERB
fcis-7982	57	14	their	their	PRON
fcis-7982	57	15	performance	performance	NOUN
fcis-7982	57	16	information	information	NOUN
fcis-7982	57	17	,	,	PUNCT
fcis-7982	57	18	but	but	CCONJ
fcis-7982	57	19	this	this	PRON
fcis-7982	57	20	will	will	AUX
fcis-7982	57	21	bring	bring	VERB
fcis-7982	57	22	huge	huge	ADJ
fcis-7982	57	23	time	time	NOUN
fcis-7982	57	24	overhead	overhead	ADV
fcis-7982	57	25	and	and	CCONJ
fcis-7982	57	26	computational	computational	ADJ
fcis-7982	57	27	cost	cost	NOUN
fcis-7982	57	28	.	.	PUNCT
fcis-7982	58	1	to	to	PART
fcis-7982	58	2	solve	solve	VERB
fcis-7982	58	3	this	this	DET
fcis-7982	58	4	problem	problem	NOUN
fcis-7982	58	5	,	,	PUNCT
fcis-7982	58	6	researchers	researcher	NOUN
fcis-7982	58	7	have	have	AUX
fcis-7982	58	8	proposed	propose	VERB
fcis-7982	58	9	the	the	DET
fcis-7982	58	10	one	one	NUM
fcis-7982	58	11	-	-	PUNCT
fcis-7982	58	12	time	time	NOUN
fcis-7982	58	13	evaluation	evaluation	NOUN
fcis-7982	58	14	method	method	NOUN
fcis-7982	58	15	.	.	PUNCT
fcis-7982	59	1	the	the	DET
fcis-7982	59	2	core	core	ADJ
fcis-7982	59	3	idea	idea	NOUN
fcis-7982	59	4	of	of	ADP
fcis-7982	59	5	the	the	DET
fcis-7982	59	6	one	one	NUM
fcis-7982	59	7	-	-	PUNCT
fcis-7982	59	8	time	time	NOUN
fcis-7982	59	9	evaluation	evaluation	NOUN
fcis-7982	59	10	method	method	NOUN
fcis-7982	59	11	is	be	AUX
fcis-7982	59	12	that	that	SCONJ
fcis-7982	59	13	the	the	DET
fcis-7982	59	14	subnets	subnet	NOUN
fcis-7982	59	15	share	share	VERB
fcis-7982	59	16	the	the	DET
fcis-7982	59	17	parameters	parameter	NOUN
fcis-7982	59	18	of	of	ADP
fcis-7982	59	19	the	the	DET
fcis-7982	59	20	supernet	supernet	NOUN
fcis-7982	59	21	and	and	CCONJ
fcis-7982	59	22	trade	trade	NOUN
fcis-7982	59	23	accuracy	accuracy	NOUN
fcis-7982	59	24	for	for	ADP
fcis-7982	59	25	speed	speed	NOUN
fcis-7982	59	26	.	.	PUNCT
fcis-7982	60	1	this	this	DET
fcis-7982	60	2	strategy	strategy	NOUN
fcis-7982	60	3	greatly	greatly	ADV
fcis-7982	60	4	reduces	reduce	VERB
fcis-7982	60	5	the	the	DET
fcis-7982	60	6	time	time	NOUN
fcis-7982	60	7	of	of	ADP
fcis-7982	60	8	the	the	DET
fcis-7982	60	9	whole	whole	ADJ
fcis-7982	60	10	process	process	NOUN
fcis-7982	60	11	and	and	CCONJ
fcis-7982	60	12	becomes	become	VERB
fcis-7982	60	13	the	the	DET
fcis-7982	60	14	current	current	ADJ
fcis-7982	60	15	3	3	NUM
fcis-7982	60	16	mainstream	mainstream	NOUN
fcis-7982	60	17	evaluation	evaluation	NOUN
fcis-7982	60	18	strategy	strategy	NOUN
fcis-7982	60	19	.	.	PUNCT
fcis-7982	61	1	in	in	ADP
fcis-7982	61	2	order	order	NOUN
fcis-7982	61	3	to	to	PART
fcis-7982	61	4	take	take	VERB
fcis-7982	61	5	full	full	ADJ
fcis-7982	61	6	advantage	advantage	NOUN
fcis-7982	61	7	of	of	ADP
fcis-7982	61	8	the	the	DET
fcis-7982	61	9	one	one	NUM
fcis-7982	61	10	-	-	PUNCT
fcis-7982	61	11	shot	shot	NOUN
fcis-7982	61	12	algorithm	algorithm	NOUN
fcis-7982	61	13	in	in	ADP
fcis-7982	61	14	microspace	microspace	NOUN
fcis-7982	61	15	,	,	PUNCT
fcis-7982	61	16	we	we	PRON
fcis-7982	61	17	make	make	VERB
fcis-7982	61	18	the	the	DET
fcis-7982	61	19	following	follow	VERB
fcis-7982	61	20	improvements	improvement	NOUN
fcis-7982	61	21	to	to	ADP
fcis-7982	61	22	the	the	DET
fcis-7982	61	23	instellar	instellar	ADJ
fcis-7982	61	24	algorithm	algorithm	NOUN
fcis-7982	61	25	.	.	PUNCT
fcis-7982	62	1	in	in	ADP
fcis-7982	62	2	the	the	DET
fcis-7982	62	3	original	original	ADJ
fcis-7982	62	4	algorithm	algorithm	NOUN
fcis-7982	62	5	,	,	PUNCT
fcis-7982	62	6	when	when	SCONJ
fcis-7982	62	7	searching	search	VERB
fcis-7982	62	8	for	for	ADP
fcis-7982	62	9	the	the	DET
fcis-7982	62	10	corresponding	corresponding	ADJ
fcis-7982	62	11	micro	micro	NOUN
fcis-7982	62	12	-	-	NOUN
fcis-7982	62	13	architecture	architecture	NOUN
fcis-7982	62	14	for	for	ADP
fcis-7982	62	15	each	each	DET
fcis-7982	62	16	macroarchitecture	macroarchitecture	NOUN
fcis-7982	62	17	,	,	PUNCT
fcis-7982	62	18	the	the	DET
fcis-7982	62	19	micro	micro	NOUN
fcis-7982	62	20	-	-	NOUN
fcis-7982	62	21	architecture	architecture	ADJ
fcis-7982	62	22	parameter	parameter	NOUN
fcis-7982	62	23	probability	probability	NOUN
fcis-7982	62	24	distribution	distribution	NOUN
fcis-7982	62	25	matrix	matrix	NOUN
fcis-7982	62	26	is	be	AUX
fcis-7982	62	27	initialized	initialize	VERB
fcis-7982	62	28	using	use	VERB
fcis-7982	62	29	the	the	DET
fcis-7982	62	30	mean	mean	ADJ
fcis-7982	62	31	value	value	NOUN
fcis-7982	62	32	method	method	NOUN
fcis-7982	62	33	.	.	PUNCT
fcis-7982	63	1	in	in	ADP
fcis-7982	63	2	order	order	NOUN
fcis-7982	63	3	that	that	SCONJ
fcis-7982	63	4	each	each	DET
fcis-7982	63	5	search	search	NOUN
fcis-7982	63	6	for	for	ADP
fcis-7982	63	7	microarchitecture	microarchitecture	NOUN
fcis-7982	63	8	can	can	AUX
fcis-7982	63	9	utilize	utilize	VERB
fcis-7982	63	10	the	the	DET
fcis-7982	63	11	information	information	NOUN
fcis-7982	63	12	from	from	ADP
fcis-7982	63	13	the	the	DET
fcis-7982	63	14	previous	previous	ADJ
fcis-7982	63	15	round	round	NOUN
fcis-7982	63	16	,	,	PUNCT
fcis-7982	63	17	we	we	PRON
fcis-7982	63	18	choose	choose	VERB
fcis-7982	63	19	to	to	PART
fcis-7982	63	20	initialize	initialize	VERB
fcis-7982	63	21	the	the	DET
fcis-7982	63	22	matrix	matrix	NOUN
fcis-7982	63	23	with	with	ADP
fcis-7982	63	24	the	the	DET
fcis-7982	63	25	updated	update	VERB
fcis-7982	63	26	probability	probability	NOUN
fcis-7982	63	27	distribution	distribution	NOUN
fcis-7982	63	28	matrix	matrix	NOUN
fcis-7982	63	29	of	of	ADP
fcis-7982	63	30	microarchitecture	microarchitecture	NOUN
fcis-7982	63	31	parameters	parameter	NOUN
fcis-7982	63	32	from	from	ADP
fcis-7982	63	33	the	the	DET
fcis-7982	63	34	previous	previous	ADJ
fcis-7982	63	35	round	round	NOUN
fcis-7982	63	36	for	for	ADP
fcis-7982	63	37	the	the	DET
fcis-7982	63	38	next	next	ADJ
fcis-7982	63	39	round	round	NOUN
fcis-7982	63	40	.	.	PUNCT
fcis-7982	64	1	the	the	DET
fcis-7982	64	2	flow	flow	NOUN
fcis-7982	64	3	of	of	ADP
fcis-7982	64	4	our	our	PRON
fcis-7982	64	5	algorithm	algorithm	NOUN
fcis-7982	64	6	is	be	AUX
fcis-7982	64	7	roughly	roughly	ADV
fcis-7982	64	8	.	.	PUNCT
fcis-7982	65	1	algorithm	algorithm	NOUN
fcis-7982	65	2	1	1	NUM
fcis-7982	65	3	initialize	initialize	VERB
fcis-7982	65	4	the	the	DET
fcis-7982	65	5	macro	macro	NOUN
fcis-7982	65	6	-	-	NOUN
fcis-7982	65	7	architecture	architecture	NOUN
fcis-7982	65	8	parameter	parameter	NOUN
fcis-7982	65	9	probability	probability	NOUN
fcis-7982	65	10	distribution	distribution	NOUN
fcis-7982	65	11	matrix	matrix	NOUN
fcis-7982	65	12	2	2	NUM
fcis-7982	65	13	sample	sample	NOUN
fcis-7982	65	14	the	the	DET
fcis-7982	65	15	macro	macro	ADJ
fcis-7982	65	16	architecture	architecture	NOUN
fcis-7982	65	17	3	3	NUM
fcis-7982	65	18	initialize	initialize	VERB
fcis-7982	65	19	the	the	DET
fcis-7982	65	20	micro	micro	NOUN
fcis-7982	65	21	-	-	NOUN
fcis-7982	65	22	architecture	architecture	ADJ
fcis-7982	65	23	parameter	parameter	NOUN
fcis-7982	65	24	probability	probability	NOUN
fcis-7982	65	25	distribution	distribution	NOUN
fcis-7982	65	26	matrix	matrix	NOUN
fcis-7982	65	27	with	with	ADP
fcis-7982	65	28	the	the	DET
fcis-7982	65	29	mean	mean	NOUN
fcis-7982	65	30	if	if	SCONJ
fcis-7982	65	31	it	it	PRON
fcis-7982	65	32	is	be	AUX
fcis-7982	65	33	the	the	DET
fcis-7982	65	34	first	first	ADJ
fcis-7982	65	35	round	round	NOUN
fcis-7982	65	36	;	;	PUNCT
fcis-7982	65	37	if	if	SCONJ
fcis-7982	65	38	it	it	PRON
fcis-7982	65	39	is	be	AUX
fcis-7982	65	40	not	not	PART
fcis-7982	65	41	the	the	DET
fcis-7982	65	42	first	first	ADJ
fcis-7982	65	43	round	round	NOUN
fcis-7982	65	44	,	,	PUNCT
fcis-7982	65	45	initialize	initialize	VERB
fcis-7982	65	46	it	it	PRON
fcis-7982	65	47	with	with	ADP
fcis-7982	65	48	the	the	DET
fcis-7982	65	49	microarchitecture	microarchitecture	NOUN
fcis-7982	65	50	probability	probability	NOUN
fcis-7982	65	51	distribution	distribution	NOUN
fcis-7982	65	52	matrix	matrix	NOUN
fcis-7982	65	53	obtained	obtain	VERB
fcis-7982	65	54	in	in	ADP
fcis-7982	65	55	the	the	DET
fcis-7982	65	56	previous	previous	ADJ
fcis-7982	65	57	round	round	NOUN
fcis-7982	65	58	.	.	PUNCT
fcis-7982	66	1	4	4	NUM
fcis-7982	66	2	neural	neural	ADJ
fcis-7982	66	3	network	network	NOUN
fcis-7982	66	4	training	training	NOUN
fcis-7982	66	5	,	,	PUNCT
fcis-7982	66	6	update	update	VERB
fcis-7982	66	7	the	the	DET
fcis-7982	66	8	micro	micro	NOUN
fcis-7982	66	9	-	-	NOUN
fcis-7982	66	10	architecture	architecture	ADJ
fcis-7982	66	11	probability	probability	NOUN
fcis-7982	66	12	distribution	distribution	NOUN
fcis-7982	66	13	matrix	matrix	NOUN
fcis-7982	66	14	by	by	ADP
fcis-7982	66	15	back	back	ADJ
fcis-7982	66	16	propagation	propagation	NOUN
fcis-7982	66	17	5	5	NUM
fcis-7982	66	18	sampling	sample	VERB
fcis-7982	66	19	micro	micro	NOUN
fcis-7982	66	20	-	-	NOUN
fcis-7982	66	21	architecture	architecture	ADJ
fcis-7982	66	22	6	6	NUM
fcis-7982	66	23	update	update	NOUN
fcis-7982	66	24	the	the	DET
fcis-7982	66	25	macro	macro	NOUN
fcis-7982	66	26	-	-	NOUN
fcis-7982	66	27	architecture	architecture	NOUN
fcis-7982	66	28	parameter	parameter	NOUN
fcis-7982	66	29	probability	probability	NOUN
fcis-7982	66	30	distribution	distribution	NOUN
fcis-7982	66	31	matrix	matrix	NOUN
fcis-7982	66	32	7	7	NUM
fcis-7982	66	33	repeat	repeat	NOUN
fcis-7982	66	34	steps	step	NOUN
fcis-7982	66	35	2	2	NUM
fcis-7982	66	36	-	-	SYM
fcis-7982	66	37	6	6	NUM
fcis-7982	66	38	until	until	SCONJ
fcis-7982	66	39	a	a	DET
fcis-7982	66	40	suitable	suitable	ADJ
fcis-7982	66	41	architecture	architecture	NOUN
fcis-7982	66	42	is	be	AUX
fcis-7982	66	43	searched	search	VERB
fcis-7982	66	44	5	5	NUM
fcis-7982	66	45	.	.	PUNCT
fcis-7982	66	46	experiment	experiment	NOUN
fcis-7982	66	47	5.1	5.1	NUM
fcis-7982	66	48	.	.	PUNCT
fcis-7982	67	1	experimental	experimental	ADJ
fcis-7982	67	2	setup	setup	NOUN
fcis-7982	67	3	we	we	PRON
fcis-7982	67	4	use	use	VERB
fcis-7982	67	5	a	a	DET
fcis-7982	67	6	biased	bias	VERB
fcis-7982	67	7	random	random	ADJ
fcis-7982	67	8	walk	walk	NOUN
fcis-7982	67	9	approach	approach	NOUN
fcis-7982	67	10	to	to	ADP
fcis-7982	67	11	sample	sample	NOUN
fcis-7982	67	12	paths	path	NOUN
fcis-7982	67	13	,	,	PUNCT
fcis-7982	67	14	using	use	VERB
fcis-7982	67	15	two	two	NUM
fcis-7982	67	16	basic	basic	ADJ
fcis-7982	67	17	tasks	task	NOUN
fcis-7982	67	18	in	in	ADP
fcis-7982	67	19	knowledge	knowledge	NOUN
fcis-7982	67	20	mapping	mapping	NOUN
fcis-7982	67	21	,	,	PUNCT
fcis-7982	67	22	entity	entity	NOUN
fcis-7982	67	23	alignment	alignment	NOUN
fcis-7982	67	24	and	and	CCONJ
fcis-7982	67	25	link	link	NOUN
fcis-7982	67	26	prediction	prediction	NOUN
fcis-7982	67	27	,	,	PUNCT
fcis-7982	67	28	as	as	ADP
fcis-7982	67	29	applicable	applicable	ADJ
fcis-7982	67	30	scenarios	scenario	NOUN
fcis-7982	67	31	.	.	PUNCT
fcis-7982	68	1	ranking	rank	VERB
fcis-7982	68	2	-	-	PUNCT
fcis-7982	68	3	based	base	VERB
fcis-7982	68	4	mrr	mrr	PROPN
fcis-7982	68	5	,	,	PUNCT
fcis-7982	68	6	hit@1	hit@1	PROPN
fcis-7982	68	7	and	and	CCONJ
fcis-7982	68	8	hit@10	hit@10	NOUN
fcis-7982	68	9	,	,	PUNCT
fcis-7982	68	10	are	be	AUX
fcis-7982	68	11	used	use	VERB
fcis-7982	68	12	as	as	ADP
fcis-7982	68	13	task	task	NOUN
fcis-7982	68	14	metrics	metric	NOUN
fcis-7982	68	15	.	.	PUNCT
fcis-7982	69	1	the	the	DET
fcis-7982	69	2	experiments	experiment	NOUN
fcis-7982	69	3	are	be	AUX
fcis-7982	69	4	run	run	VERB
fcis-7982	69	5	on	on	ADP
fcis-7982	69	6	a	a	DET
fcis-7982	69	7	single	single	ADJ
fcis-7982	69	8	geforce	geforce	NOUN
fcis-7982	69	9	rtx3090	rtx3090	VERB
fcis-7982	69	10	64	64	NUM
fcis-7982	69	11	gb	gb	NOUN
fcis-7982	69	12	using	use	VERB
fcis-7982	69	13	the	the	DET
fcis-7982	69	14	pytorch	pytorch	NOUN
fcis-7982	69	15	framework	framework	NOUN
fcis-7982	69	16	[	[	X
fcis-7982	69	17	7	7	NUM
fcis-7982	69	18	]	]	PUNCT
fcis-7982	69	19	.	.	PUNCT
fcis-7982	70	1	5.2	5.2	NUM
fcis-7982	70	2	.	.	PUNCT
fcis-7982	70	3	introduction	introduction	NOUN
fcis-7982	70	4	to	to	ADP
fcis-7982	70	5	the	the	DET
fcis-7982	70	6	experimental	experimental	ADJ
fcis-7982	70	7	dataset	dataset	NOUN
fcis-7982	70	8	for	for	ADP
fcis-7982	70	9	the	the	DET
fcis-7982	70	10	entity	entity	NOUN
fcis-7982	70	11	alignment	alignment	NOUN
fcis-7982	70	12	task	task	NOUN
fcis-7982	70	13	,	,	PUNCT
fcis-7982	70	14	we	we	PRON
fcis-7982	70	15	chose	choose	VERB
fcis-7982	70	16	three	three	NUM
fcis-7982	70	17	crosslanguage	crosslanguage	NOUN
fcis-7982	70	18	and	and	CCONJ
fcis-7982	70	19	cross	cross	ADJ
fcis-7982	70	20	-	-	ADJ
fcis-7982	70	21	database	database	ADJ
fcis-7982	70	22	datasets	dataset	NOUN
fcis-7982	70	23	,	,	PUNCT
fcis-7982	70	24	which	which	PRON
fcis-7982	70	25	are	be	AUX
fcis-7982	70	26	subsets	subset	NOUN
fcis-7982	70	27	of	of	ADP
fcis-7982	70	28	dbpedia	dbpedia	PROPN
fcis-7982	70	29	and	and	CCONJ
fcis-7982	70	30	wikidata	wikidata	NOUN
fcis-7982	70	31	,	,	PUNCT
fcis-7982	70	32	namely	namely	ADV
fcis-7982	70	33	dbp	dbp	PROPN
fcis-7982	70	34	-	-	PUNCT
fcis-7982	70	35	wd	wd	PROPN
fcis-7982	70	36	,	,	PUNCT
fcis-7982	70	37	en	en	NOUN
fcis-7982	70	38	-	-	ADJ
fcis-7982	70	39	fr	fr	ADJ
fcis-7982	70	40	,	,	PUNCT
fcis-7982	70	41	and	and	CCONJ
fcis-7982	70	42	ende	ende	NOUN
fcis-7982	70	43	.	.	PUNCT
fcis-7982	71	1	for	for	ADP
fcis-7982	71	2	each	each	DET
fcis-7982	71	3	dataset	dataset	NOUN
fcis-7982	71	4	,	,	PUNCT
fcis-7982	71	5	by	by	ADP
fcis-7982	71	6	divided	divide	VERB
fcis-7982	71	7	into	into	ADP
fcis-7982	71	8	normal	normal	ADJ
fcis-7982	71	9	and	and	CCONJ
fcis-7982	71	10	dense	dense	ADJ
fcis-7982	71	11	versions	version	NOUN
fcis-7982	71	12	.	.	PUNCT
fcis-7982	72	1	the	the	DET
fcis-7982	72	2	normal	normal	ADJ
fcis-7982	72	3	version	version	NOUN
fcis-7982	72	4	of	of	ADP
fcis-7982	72	5	the	the	DET
fcis-7982	72	6	dataset	dataset	NOUN
fcis-7982	72	7	samples	sample	NOUN
fcis-7982	72	8	the	the	DET
fcis-7982	72	9	triples	triple	NOUN
fcis-7982	72	10	with	with	ADP
fcis-7982	72	11	degrees	degree	NOUN
fcis-7982	72	12	that	that	PRON
fcis-7982	72	13	approximate	approximate	VERB
fcis-7982	72	14	the	the	DET
fcis-7982	72	15	nodes	node	NOUN
fcis-7982	72	16	in	in	ADP
fcis-7982	72	17	the	the	DET
fcis-7982	72	18	original	original	ADJ
fcis-7982	72	19	knowledge	knowledge	NOUN
fcis-7982	72	20	graph	graph	NOUN
fcis-7982	72	21	.	.	PUNCT
fcis-7982	73	1	this	this	DET
fcis-7982	73	2	sampling	sampling	NOUN
fcis-7982	73	3	method	method	NOUN
fcis-7982	73	4	makes	make	VERB
fcis-7982	73	5	the	the	DET
fcis-7982	73	6	dataset	dataset	NOUN
fcis-7982	73	7	more	more	ADV
fcis-7982	73	8	realistic	realistic	ADJ
fcis-7982	73	9	and	and	CCONJ
fcis-7982	73	10	closer	close	ADJ
fcis-7982	73	11	to	to	ADP
fcis-7982	73	12	the	the	DET
fcis-7982	73	13	original	original	ADJ
fcis-7982	73	14	knowledge	knowledge	NOUN
fcis-7982	73	15	graph	graph	NOUN
fcis-7982	73	16	.	.	PUNCT
fcis-7982	74	1	the	the	DET
fcis-7982	74	2	dense	dense	ADJ
fcis-7982	74	3	version	version	NOUN
fcis-7982	74	4	of	of	ADP
fcis-7982	74	5	the	the	DET
fcis-7982	74	6	dataset	dataset	NOUN
fcis-7982	74	7	randomly	randomly	ADV
fcis-7982	74	8	removes	remove	VERB
fcis-7982	74	9	the	the	DET
fcis-7982	74	10	entities	entity	NOUN
fcis-7982	74	11	with	with	ADP
fcis-7982	74	12	lower	low	ADJ
fcis-7982	74	13	degrees	degree	NOUN
fcis-7982	74	14	from	from	ADP
fcis-7982	74	15	the	the	DET
fcis-7982	74	16	original	original	ADJ
fcis-7982	74	17	knowledge	knowledge	NOUN
fcis-7982	74	18	graph	graph	NOUN
fcis-7982	74	19	.	.	PUNCT
fcis-7982	75	1	this	this	DET
fcis-7982	75	2	version	version	NOUN
fcis-7982	75	3	of	of	ADP
fcis-7982	75	4	the	the	DET
fcis-7982	75	5	dataset	dataset	NOUN
fcis-7982	75	6	more	more	ADV
fcis-7982	75	7	closely	closely	ADV
fcis-7982	75	8	resembles	resemble	VERB
fcis-7982	75	9	the	the	DET
fcis-7982	75	10	dataset	dataset	NOUN
fcis-7982	75	11	used	use	VERB
fcis-7982	75	12	by	by	ADP
fcis-7982	75	13	existing	exist	VERB
fcis-7982	75	14	methods	method	NOUN
fcis-7982	75	15	[	[	X
fcis-7982	75	16	8	8	NUM
fcis-7982	75	17	]	]	PUNCT
fcis-7982	75	18	.	.	PUNCT
fcis-7982	76	1	for	for	ADP
fcis-7982	76	2	the	the	DET
fcis-7982	76	3	link	link	NOUN
fcis-7982	76	4	prediction	prediction	NOUN
fcis-7982	76	5	task	task	NOUN
fcis-7982	76	6	,	,	PUNCT
fcis-7982	76	7	the	the	DET
fcis-7982	76	8	commonly	commonly	ADV
fcis-7982	76	9	used	use	VERB
fcis-7982	76	10	datasets	dataset	NOUN
fcis-7982	76	11	are	be	AUX
fcis-7982	76	12	wn18	wn18	PROPN
fcis-7982	76	13	and	and	CCONJ
fcis-7982	76	14	fb15	fb15	PROPN
fcis-7982	76	15	,	,	PUNCT
fcis-7982	76	16	but	but	CCONJ
fcis-7982	76	17	they	they	PRON
fcis-7982	76	18	are	be	AUX
fcis-7982	76	19	prone	prone	ADJ
fcis-7982	76	20	to	to	PART
fcis-7982	76	21	test	test	VERB
fcis-7982	76	22	leakage	leakage	NOUN
fcis-7982	76	23	through	through	ADP
fcis-7982	76	24	inverse	inverse	NOUN
fcis-7982	76	25	relations	relation	NOUN
fcis-7982	76	26	.	.	PUNCT
fcis-7982	77	1	that	that	PRON
fcis-7982	77	2	is	is	ADV
fcis-7982	77	3	,	,	PUNCT
fcis-7982	77	4	the	the	DET
fcis-7982	77	5	test	test	NOUN
fcis-7982	77	6	triples	triple	NOUN
fcis-7982	77	7	often	often	ADV
fcis-7982	77	8	contain	contain	VERB
fcis-7982	77	9	many	many	ADJ
fcis-7982	77	10	triples	triple	NOUN
fcis-7982	77	11	obtained	obtain	VERB
fcis-7982	77	12	by	by	ADP
fcis-7982	77	13	performing	perform	VERB
fcis-7982	77	14	inverse	inverse	NOUN
fcis-7982	77	15	operations	operation	NOUN
fcis-7982	77	16	on	on	ADP
fcis-7982	77	17	the	the	DET
fcis-7982	77	18	triples	triple	NOUN
fcis-7982	77	19	in	in	ADP
fcis-7982	77	20	the	the	DET
fcis-7982	77	21	training	training	NOUN
fcis-7982	77	22	set	set	NOUN
fcis-7982	77	23	.	.	PUNCT
fcis-7982	78	1	to	to	PART
fcis-7982	78	2	solve	solve	VERB
fcis-7982	78	3	the	the	DET
fcis-7982	78	4	problem	problem	NOUN
fcis-7982	78	5	of	of	ADP
fcis-7982	78	6	link	link	NOUN
fcis-7982	78	7	leakage	leakage	NOUN
fcis-7982	78	8	,	,	PUNCT
fcis-7982	78	9	datasets	dataset	VERB
fcis-7982	78	10	wn18	wn18	PROPN
fcis-7982	78	11	-	-	PUNCT
fcis-7982	78	12	rr	rr	PROPN
fcis-7982	78	13	and	and	CCONJ
fcis-7982	78	14	fb15k-237	fb15k-237	PROPN
fcis-7982	78	15	,	,	PUNCT
fcis-7982	78	16	which	which	PRON
fcis-7982	78	17	are	be	AUX
fcis-7982	78	18	subsets	subset	NOUN
fcis-7982	78	19	of	of	ADP
fcis-7982	78	20	datasets	dataset	NOUN
fcis-7982	78	21	wn18	wn18	PROPN
fcis-7982	78	22	and	and	CCONJ
fcis-7982	78	23	fb15	fb15	PROPN
fcis-7982	78	24	,	,	PUNCT
fcis-7982	78	25	have	have	AUX
fcis-7982	78	26	been	be	AUX
fcis-7982	78	27	created	create	VERB
fcis-7982	78	28	without	without	ADP
fcis-7982	78	29	inverse	inverse	NOUN
fcis-7982	78	30	relations	relation	NOUN
fcis-7982	78	31	.	.	PUNCT
fcis-7982	79	1	table	table	NOUN
fcis-7982	79	2	2	2	NUM
fcis-7982	79	3	.	.	PUNCT
fcis-7982	79	4	dataset	dataset	PROPN
fcis-7982	79	5	version	version	PROPN
fcis-7982	79	6	data	data	PROPN
fcis-7982	79	7	source	source	NOUN
fcis-7982	79	8	dbp	dbp	PROPN
fcis-7982	79	9	-	-	PUNCT
fcis-7982	79	10	wd	wd	PROPN
fcis-7982	79	11	en	en	PROPN
fcis-7982	79	12	-	-	X
fcis-7982	79	13	de	de	X
fcis-7982	79	14	en	en	PROPN
fcis-7982	79	15	-	-	ADJ
fcis-7982	79	16	fr	fr	ADJ
fcis-7982	79	17	dbpedia	dbpedia	PROPN
fcis-7982	79	18	wikidata	wikidata	PROPN
fcis-7982	79	19	english	english	PROPN
fcis-7982	79	20	french	french	ADJ
fcis-7982	79	21	english	english	ADJ
fcis-7982	79	22	german	german	ADJ
fcis-7982	79	23	normal	normal	ADJ
fcis-7982	79	24	version	version	NOUN
fcis-7982	79	25	number	number	NOUN
fcis-7982	79	26	of	of	ADP
fcis-7982	79	27	relationships	relationship	NOUN
fcis-7982	79	28	253	253	NUM
fcis-7982	79	29	144	144	NUM
fcis-7982	79	30	211	211	NUM
fcis-7982	79	31	177	177	NUM
fcis-7982	79	32	225	225	NUM
fcis-7982	79	33	118	118	NUM
fcis-7982	79	34	number	number	NOUN
fcis-7982	79	35	of	of	ADP
fcis-7982	79	36	entities	entity	NOUN
fcis-7982	79	37	38421	38421	NUM
fcis-7982	79	38	40159	40159	NUM
fcis-7982	79	39	36508	36508	NUM
fcis-7982	79	40	33532	33532	NUM
fcis-7982	79	41	38281	38281	NUM
fcis-7982	79	42	37069	37069	NUM
fcis-7982	79	43	dense	dense	ADJ
fcis-7982	79	44	version	version	NOUN
fcis-7982	79	45	number	number	NOUN
fcis-7982	79	46	of	of	ADP
fcis-7982	79	47	relationships	relationship	NOUN
fcis-7982	79	48	220	220	NUM
fcis-7982	79	49	135	135	NUM
fcis-7982	79	50	217	217	NUM
fcis-7982	79	51	174	174	NUM
fcis-7982	79	52	207	207	NUM
fcis-7982	79	53	117	117	NUM
fcis-7982	79	54	number	number	NOUN
fcis-7982	79	55	of	of	ADP
fcis-7982	79	56	entities	entity	NOUN
fcis-7982	79	57	68598	68598	NUM
fcis-7982	79	58	75465	75465	NUM
fcis-7982	79	59	71929	71929	NUM
fcis-7982	79	60	66760	66760	NUM
fcis-7982	79	61	56983	56983	NUM
fcis-7982	79	62	59848	59848	NUM
fcis-7982	79	63	table	table	NOUN
fcis-7982	79	64	3	3	NUM
fcis-7982	79	65	.	.	PUNCT
fcis-7982	79	66	data	datum	NOUN
fcis-7982	79	67	sets	set	NOUN
fcis-7982	79	68	without	without	ADP
fcis-7982	79	69	inverse	inverse	NOUN
fcis-7982	79	70	relations	relation	NOUN
fcis-7982	79	71	dataset	dataset	NOUN
fcis-7982	79	72	number	number	NOUN
fcis-7982	79	73	of	of	ADP
fcis-7982	79	74	entities	entity	NOUN
fcis-7982	79	75	number	number	NOUN
fcis-7982	79	76	of	of	ADP
fcis-7982	79	77	relationships	relationship	NOUN
fcis-7982	79	78	number	number	NOUN
fcis-7982	79	79	of	of	ADP
fcis-7982	79	80	entity	entity	NOUN
fcis-7982	79	81	pairs	pair	NOUN
fcis-7982	79	82	in	in	ADP
fcis-7982	79	83	the	the	DET
fcis-7982	79	84	training	training	NOUN
fcis-7982	79	85	set	set	NOUN
fcis-7982	79	86	number	number	NOUN
fcis-7982	79	87	of	of	ADP
fcis-7982	79	88	entities	entity	NOUN
fcis-7982	79	89	pairs	pair	NOUN
fcis-7982	79	90	in	in	ADP
fcis-7982	79	91	the	the	DET
fcis-7982	79	92	validation	validation	NOUN
fcis-7982	79	93	set	set	VERB
fcis-7982	79	94	number	number	NOUN
fcis-7982	79	95	of	of	ADP
fcis-7982	79	96	entity	entity	NOUN
fcis-7982	79	97	pairs	pair	NOUN
fcis-7982	79	98	in	in	ADP
fcis-7982	79	99	the	the	DET
fcis-7982	79	100	test	test	NOUN
fcis-7982	79	101	set	set	VERB
fcis-7982	79	102	wn18rr	wn18rr	PROPN
fcis-7982	79	103	40943	40943	NUM
fcis-7982	79	104	11	11	NUM
fcis-7982	79	105	86835	86835	NUM
fcis-7982	79	106	3034	3034	NUM
fcis-7982	79	107	3134	3134	NUM
fcis-7982	79	108	fb15k37	fb15k37	PROPN
fcis-7982	79	109	14541	14541	NUM
fcis-7982	79	110	237	237	NUM
fcis-7982	79	111	272115	272115	NUM
fcis-7982	79	112	17536	17536	NUM
fcis-7982	79	113	20466	20466	NUM
fcis-7982	79	114	5.3	5.3	NUM
fcis-7982	79	115	.	.	PUNCT
fcis-7982	80	1	experimental	experimental	ADJ
fcis-7982	80	2	results	result	NOUN
fcis-7982	80	3	and	and	CCONJ
fcis-7982	80	4	analysis	analysis	NOUN
fcis-7982	80	5	the	the	DET
fcis-7982	80	6	metrics	metric	NOUN
fcis-7982	80	7	commonly	commonly	ADV
fcis-7982	80	8	used	use	VERB
fcis-7982	80	9	for	for	ADP
fcis-7982	80	10	the	the	DET
fcis-7982	80	11	evaluation	evaluation	NOUN
fcis-7982	80	12	of	of	ADP
fcis-7982	80	13	knowledge	knowledge	NOUN
fcis-7982	80	14	graph	graph	NOUN
fcis-7982	80	15	embedding	embed	VERB
fcis-7982	80	16	tasks	task	NOUN
fcis-7982	80	17	are	be	AUX
fcis-7982	80	18	mrr	mrr	NOUN
fcis-7982	80	19	,	,	PUNCT
fcis-7982	80	20	hit@1	hit@1	PROPN
fcis-7982	80	21	,	,	PUNCT
fcis-7982	80	22	hit@10	hit@10	PROPN
fcis-7982	80	23	,	,	PUNCT
fcis-7982	80	24	etc	etc	X
fcis-7982	80	25	.	.	X
fcis-7982	81	1	since	since	SCONJ
fcis-7982	81	2	the	the	DET
fcis-7982	81	3	performance	performance	NOUN
fcis-7982	81	4	of	of	ADP
fcis-7982	81	5	an	an	DET
fcis-7982	81	6	architecture	architecture	NOUN
fcis-7982	81	7	is	be	AUX
fcis-7982	81	8	objective	objective	ADJ
fcis-7982	81	9	and	and	CCONJ
fcis-7982	81	10	does	do	AUX
fcis-7982	81	11	not	not	PART
fcis-7982	81	12	vary	vary	VERB
fcis-7982	81	13	substantially	substantially	ADV
fcis-7982	81	14	with	with	ADP
fcis-7982	81	15	the	the	DET
fcis-7982	81	16	measurement	measurement	NOUN
fcis-7982	81	17	metrics	metric	NOUN
fcis-7982	81	18	,	,	PUNCT
fcis-7982	81	19	next	next	ADV
fcis-7982	81	20	,	,	PUNCT
fcis-7982	81	21	we	we	PRON
fcis-7982	81	22	perform	perform	VERB
fcis-7982	81	23	the	the	DET
fcis-7982	81	24	result	result	NOUN
fcis-7982	81	25	comparison	comparison	NOUN
fcis-7982	81	26	with	with	ADP
fcis-7982	81	27	hit@1	hit@1	PROPN
fcis-7982	81	28	as	as	ADP
fcis-7982	81	29	the	the	DET
fcis-7982	81	30	main	main	ADJ
fcis-7982	81	31	evaluation	evaluation	NOUN
fcis-7982	81	32	metric	metric	NOUN
fcis-7982	81	33	for	for	ADP
fcis-7982	81	34	the	the	DET
fcis-7982	81	35	search	search	NOUN
fcis-7982	81	36	process	process	NOUN
fcis-7982	81	37	demonstration	demonstration	NOUN
fcis-7982	81	38	.	.	PUNCT
fcis-7982	82	1	for	for	ADP
fcis-7982	82	2	a	a	DET
fcis-7982	82	3	fair	fair	ADJ
fcis-7982	82	4	comparison	comparison	NOUN
fcis-7982	82	5	,	,	PUNCT
fcis-7982	82	6	we	we	PRON
fcis-7982	82	7	take	take	VERB
fcis-7982	82	8	the	the	DET
fcis-7982	82	9	same	same	ADJ
fcis-7982	82	10	path	path	NOUN
fcis-7982	82	11	sampling	sample	VERB
fcis-7982	82	12	scheme	scheme	NOUN
fcis-7982	82	13	and	and	CCONJ
fcis-7982	82	14	data	datum	NOUN
fcis-7982	82	15	partitioning	partition	VERB
fcis-7982	82	16	scheme	scheme	NOUN
fcis-7982	82	17	on	on	ADP
fcis-7982	82	18	each	each	DET
fcis-7982	82	19	dataset	dataset	NOUN
fcis-7982	82	20	.	.	PUNCT
fcis-7982	83	1	the	the	DET
fcis-7982	83	2	following	follow	VERB
fcis-7982	83	3	line	line	NOUN
fcis-7982	83	4	graph	graph	NOUN
fcis-7982	83	5	gives	give	VERB
fcis-7982	83	6	a	a	DET
fcis-7982	83	7	comparison	comparison	NOUN
fcis-7982	83	8	of	of	ADP
fcis-7982	83	9	the	the	DET
fcis-7982	83	10	performance	performance	NOUN
fcis-7982	83	11	of	of	ADP
fcis-7982	83	12	the	the	DET
fcis-7982	83	13	original	original	ADJ
fcis-7982	83	14	algorithm	algorithm	NOUN
fcis-7982	83	15	and	and	CCONJ
fcis-7982	83	16	the	the	DET
fcis-7982	83	17	improved	improved	ADJ
fcis-7982	83	18	algorithm	algorithm	NOUN
fcis-7982	83	19	searching	search	VERB
fcis-7982	83	20	out	out	ADP
fcis-7982	83	21	the	the	DET
fcis-7982	83	22	architecture	architecture	NOUN
fcis-7982	83	23	on	on	ADP
fcis-7982	83	24	different	different	ADJ
fcis-7982	83	25	datasets	dataset	NOUN
fcis-7982	83	26	.	.	PUNCT
fcis-7982	84	1	the	the	DET
fcis-7982	84	2	solid	solid	ADJ
fcis-7982	84	3	blue	blue	ADJ
fcis-7982	84	4	line	line	NOUN
fcis-7982	84	5	represents	represent	VERB
fcis-7982	84	6	the	the	DET
fcis-7982	84	7	architecture	architecture	NOUN
fcis-7982	84	8	searched	search	VERB
fcis-7982	84	9	by	by	ADP
fcis-7982	84	10	the	the	DET
fcis-7982	84	11	original	original	ADJ
fcis-7982	84	12	algorithm	algorithm	NOUN
fcis-7982	84	13	,	,	PUNCT
fcis-7982	84	14	the	the	DET
fcis-7982	84	15	dashed	dash	VERB
fcis-7982	84	16	green	green	ADJ
fcis-7982	84	17	line	line	NOUN
fcis-7982	84	18	represents	represent	VERB
fcis-7982	84	19	the	the	DET
fcis-7982	84	20	improved	improved	ADJ
fcis-7982	84	21	algorithm	algorithm	NOUN
fcis-7982	84	22	,	,	PUNCT
fcis-7982	84	23	and	and	CCONJ
fcis-7982	84	24	the	the	DET
fcis-7982	84	25	red	red	ADJ
fcis-7982	84	26	implementation	implementation	NOUN
fcis-7982	84	27	represents	represent	VERB
fcis-7982	84	28	the	the	DET
fcis-7982	84	29	optimal	optimal	ADJ
fcis-7982	84	30	neural	neural	ADJ
fcis-7982	84	31	architecture	architecture	NOUN
fcis-7982	84	32	currently	currently	ADV
fcis-7982	84	33	designed	design	VERB
fcis-7982	84	34	by	by	ADP
fcis-7982	84	35	humans	human	NOUN
fcis-7982	84	36	on	on	ADP
fcis-7982	84	37	this	this	DET
fcis-7982	84	38	dataset	dataset	NOUN
fcis-7982	84	39	.	.	PUNCT
fcis-7982	85	1	as	as	SCONJ
fcis-7982	85	2	can	can	AUX
fcis-7982	85	3	be	be	AUX
fcis-7982	85	4	seen	see	VERB
fcis-7982	85	5	from	from	ADP
fcis-7982	85	6	the	the	DET
fcis-7982	85	7	line	line	NOUN
fcis-7982	85	8	graph	graph	NOUN
fcis-7982	85	9	,	,	PUNCT
fcis-7982	85	10	the	the	DET
fcis-7982	85	11	performance	performance	NOUN
fcis-7982	85	12	of	of	ADP
fcis-7982	85	13	the	the	DET
fcis-7982	85	14	optimal	optimal	ADJ
fcis-7982	85	15	architectures	architecture	NOUN
fcis-7982	85	16	searched	search	VERB
fcis-7982	85	17	in	in	ADP
fcis-7982	85	18	the	the	DET
fcis-7982	85	19	dbp_wd	dbp_wd	PROPN
fcis-7982	85	20	,	,	PUNCT
fcis-7982	85	21	en_de	en_de	NOUN
fcis-7982	85	22	datasets	dataset	NOUN
fcis-7982	85	23	after	after	ADP
fcis-7982	85	24	adding	add	VERB
fcis-7982	85	25	the	the	DET
fcis-7982	85	26	clustering	clustering	ADJ
fcis-7982	85	27	algorithm	algorithm	NOUN
fcis-7982	85	28	are	be	AUX
fcis-7982	85	29	close	close	ADJ
fcis-7982	85	30	to	to	ADP
fcis-7982	85	31	or	or	CCONJ
fcis-7982	85	32	higher	high	ADJ
fcis-7982	85	33	than	than	ADP
fcis-7982	85	34	the	the	DET
fcis-7982	85	35	performance	performance	NOUN
fcis-7982	85	36	of	of	ADP
fcis-7982	85	37	the	the	DET
fcis-7982	85	38	optimal	optimal	ADJ
fcis-7982	85	39	architectures	architecture	NOUN
fcis-7982	85	40	searched	search	VERB
fcis-7982	85	41	by	by	ADP
fcis-7982	85	42	the	the	DET
fcis-7982	85	43	original	original	ADJ
fcis-7982	85	44	search	search	NOUN
fcis-7982	85	45	algorithm	algorithm	NOUN
fcis-7982	85	46	.	.	PUNCT
fcis-7982	86	1	among	among	ADP
fcis-7982	86	2	them	they	PRON
fcis-7982	86	3	,	,	PUNCT
fcis-7982	86	4	the	the	DET
fcis-7982	86	5	performance	performance	NOUN
fcis-7982	86	6	of	of	ADP
fcis-7982	86	7	the	the	DET
fcis-7982	86	8	optimal	optimal	ADJ
fcis-7982	86	9	architecture	architecture	NOUN
fcis-7982	86	10	searched	search	VERB
fcis-7982	86	11	in	in	ADP
fcis-7982	86	12	the	the	DET
fcis-7982	86	13	dense	dense	ADJ
fcis-7982	86	14	version	version	NOUN
fcis-7982	86	15	of	of	ADP
fcis-7982	86	16	dbp	dbp	PROPN
fcis-7982	86	17	-	-	PUNCT
fcis-7982	86	18	wd	wd	PROPN
fcis-7982	86	19	dataset	dataset	NOUN
fcis-7982	86	20	is	be	AUX
fcis-7982	86	21	better	well	ADJ
fcis-7982	86	22	than	than	ADP
fcis-7982	86	23	the	the	DET
fcis-7982	86	24	performance	performance	NOUN
fcis-7982	86	25	of	of	ADP
fcis-7982	86	26	the	the	DET
fcis-7982	86	27	current	current	ADJ
fcis-7982	86	28	human	human	ADJ
fcis-7982	86	29	hand	hand	NOUN
fcis-7982	86	30	-	-	PUNCT
fcis-7982	86	31	designed	design	VERB
fcis-7982	86	32	architecture	architecture	NOUN
fcis-7982	86	33	.	.	PUNCT
fcis-7982	87	1	the	the	DET
fcis-7982	87	2	algorithm	algorithm	NOUN
fcis-7982	87	3	searched	search	VERB
fcis-7982	87	4	the	the	DET
fcis-7982	87	5	first	first	ADJ
fcis-7982	87	6	thirty	thirty	NUM
fcis-7982	87	7	search	search	NOUN
fcis-7982	87	8	rounds	round	NOUN
fcis-7982	87	9	and	and	CCONJ
fcis-7982	87	10	found	find	VERB
fcis-7982	87	11	architectures	architecture	NOUN
fcis-7982	87	12	that	that	PRON
fcis-7982	87	13	were	be	AUX
fcis-7982	87	14	very	very	ADV
fcis-7982	87	15	close	close	ADJ
fcis-7982	87	16	to	to	ADP
fcis-7982	87	17	the	the	DET
fcis-7982	87	18	performance	performance	NOUN
fcis-7982	87	19	of	of	ADP
fcis-7982	87	20	the	the	DET
fcis-7982	87	21	human	human	ADJ
fcis-7982	87	22	hand	hand	NOUN
fcis-7982	87	23	-	-	PUNCT
fcis-7982	87	24	designed	design	VERB
fcis-7982	87	25	optimal	optimal	ADJ
fcis-7982	87	26	architecture	architecture	NOUN
fcis-7982	87	27	.	.	PUNCT
fcis-7982	88	1	this	this	PRON
fcis-7982	88	2	demonstrates	demonstrate	VERB
fcis-7982	88	3	that	that	SCONJ
fcis-7982	88	4	our	our	PRON
fcis-7982	88	5	improvement	improvement	NOUN
fcis-7982	88	6	of	of	ADP
fcis-7982	88	7	the	the	DET
fcis-7982	88	8	search	search	NOUN
fcis-7982	88	9	strategy	strategy	NOUN
fcis-7982	88	10	is	be	AUX
fcis-7982	88	11	effective	effective	ADJ
fcis-7982	88	12	and	and	CCONJ
fcis-7982	88	13	enables	enable	VERB
fcis-7982	88	14	the	the	DET
fcis-7982	88	15	algorithm	algorithm	NOUN
fcis-7982	88	16	to	to	PART
fcis-7982	88	17	search	search	VERB
fcis-7982	88	18	for	for	ADP
fcis-7982	88	19	better	well	ADJ
fcis-7982	88	20	performing	perform	VERB
fcis-7982	88	21	architectures	architecture	NOUN
fcis-7982	88	22	based	base	VERB
fcis-7982	88	23	on	on	ADP
fcis-7982	88	24	the	the	DET
fcis-7982	88	25	original	original	ADJ
fcis-7982	88	26	4	4	NUM
fcis-7982	88	27	search	search	NOUN
fcis-7982	88	28	architecture	architecture	NOUN
fcis-7982	88	29	.	.	PUNCT
fcis-7982	89	1	figure	figure	NOUN
fcis-7982	89	2	2	2	NUM
fcis-7982	89	3	.	.	PUNCT
fcis-7982	89	4	experimental	experimental	ADJ
fcis-7982	89	5	results	result	NOUN
fcis-7982	89	6	and	and	CCONJ
fcis-7982	89	7	demonstration	demonstration	NOUN
fcis-7982	89	8	6	6	NUM
fcis-7982	89	9	.	.	PUNCT
fcis-7982	90	1	conclusion	conclusion	NOUN
fcis-7982	90	2	and	and	CCONJ
fcis-7982	90	3	outlook	outlook	NOUN
fcis-7982	90	4	knowledge	knowledge	NOUN
fcis-7982	90	5	graph	graph	NOUN
fcis-7982	90	6	embedding	embed	VERB
fcis-7982	90	7	is	be	AUX
fcis-7982	90	8	a	a	DET
fcis-7982	90	9	very	very	ADV
fcis-7982	90	10	important	important	ADJ
fcis-7982	90	11	form	form	NOUN
fcis-7982	90	12	of	of	ADP
fcis-7982	90	13	knowledge	knowledge	NOUN
fcis-7982	90	14	graph	graph	NOUN
fcis-7982	90	15	representation	representation	NOUN
fcis-7982	90	16	.	.	PUNCT
fcis-7982	91	1	existing	exist	VERB
fcis-7982	91	2	knowledge	knowledge	NOUN
fcis-7982	91	3	graph	graph	NOUN
fcis-7982	91	4	embedding	embed	VERB
fcis-7982	91	5	models	model	NOUN
fcis-7982	91	6	have	have	VERB
fcis-7982	91	7	limited	limit	VERB
fcis-7982	91	8	scalability	scalability	NOUN
fcis-7982	91	9	and	and	CCONJ
fcis-7982	91	10	are	be	AUX
fcis-7982	91	11	required	require	VERB
fcis-7982	91	12	for	for	ADP
fcis-7982	91	13	both	both	CCONJ
fcis-7982	91	14	downstream	downstream	ADJ
fcis-7982	91	15	tasks	task	NOUN
fcis-7982	91	16	and	and	CCONJ
fcis-7982	91	17	datasets	dataset	NOUN
fcis-7982	91	18	of	of	ADP
fcis-7982	91	19	knowledge	knowledge	NOUN
fcis-7982	91	20	graphs	graph	NOUN
fcis-7982	91	21	.	.	PUNCT
fcis-7982	92	1	existing	exist	VERB
fcis-7982	92	2	approaches	approach	NOUN
fcis-7982	92	3	combine	combine	VERB
fcis-7982	92	4	neural	neural	ADJ
fcis-7982	92	5	network	network	NOUN
fcis-7982	92	6	architecture	architecture	NOUN
fcis-7982	92	7	search	search	NOUN
fcis-7982	92	8	with	with	ADP
fcis-7982	92	9	knowledge	knowledge	NOUN
fcis-7982	92	10	graph	graph	NOUN
fcis-7982	92	11	embedding	embed	VERB
fcis-7982	92	12	.	.	PUNCT
fcis-7982	93	1	we	we	PRON
fcis-7982	93	2	further	far	ADV
fcis-7982	93	3	perform	perform	VERB
fcis-7982	93	4	algorithm	algorithm	NOUN
fcis-7982	93	5	optimization	optimization	NOUN
fcis-7982	93	6	based	base	VERB
fcis-7982	93	7	on	on	ADP
fcis-7982	93	8	the	the	DET
fcis-7982	93	9	interstellar	interstellar	ADJ
fcis-7982	93	10	algorithm	algorithm	NOUN
fcis-7982	93	11	to	to	PART
fcis-7982	93	12	improve	improve	VERB
fcis-7982	93	13	the	the	DET
fcis-7982	93	14	initialization	initialization	NOUN
fcis-7982	93	15	method	method	NOUN
fcis-7982	93	16	of	of	ADP
fcis-7982	93	17	the	the	DET
fcis-7982	93	18	probability	probability	NOUN
fcis-7982	93	19	distribution	distribution	NOUN
fcis-7982	93	20	matrix	matrix	NOUN
fcis-7982	93	21	of	of	ADP
fcis-7982	93	22	microscopic	microscopic	ADJ
fcis-7982	93	23	parameters	parameter	NOUN
fcis-7982	93	24	.	.	PUNCT
fcis-7982	94	1	after	after	ADP
fcis-7982	94	2	validation	validation	NOUN
fcis-7982	94	3	on	on	ADP
fcis-7982	94	4	different	different	ADJ
fcis-7982	94	5	downstream	downstream	ADJ
fcis-7982	94	6	tasks	task	NOUN
fcis-7982	94	7	and	and	CCONJ
fcis-7982	94	8	datasets	dataset	NOUN
fcis-7982	94	9	of	of	ADP
fcis-7982	94	10	the	the	DET
fcis-7982	94	11	knowledge	knowledge	NOUN
fcis-7982	94	12	graph	graph	NOUN
fcis-7982	94	13	,	,	PUNCT
fcis-7982	94	14	our	our	PRON
fcis-7982	94	15	improvements	improvement	NOUN
fcis-7982	94	16	are	be	AUX
fcis-7982	94	17	found	find	VERB
fcis-7982	94	18	to	to	PART
fcis-7982	94	19	be	be	AUX
fcis-7982	94	20	effective	effective	ADJ
fcis-7982	94	21	and	and	CCONJ
fcis-7982	94	22	improve	improve	VERB
fcis-7982	94	23	the	the	DET
fcis-7982	94	24	search	search	NOUN
fcis-7982	94	25	efficiency	efficiency	NOUN
fcis-7982	94	26	.	.	PUNCT
fcis-7982	95	1	in	in	ADP
fcis-7982	95	2	reference	reference	NOUN
fcis-7982	95	3	[	[	X
fcis-7982	95	4	7	7	NUM
fcis-7982	95	5	]	]	PUNCT
fcis-7982	95	6	,	,	PUNCT
fcis-7982	95	7	researchers	researcher	NOUN
fcis-7982	95	8	applied	apply	VERB
fcis-7982	95	9	neural	neural	ADJ
fcis-7982	95	10	architecture	architecture	NOUN
fcis-7982	95	11	search	search	NOUN
fcis-7982	95	12	techniques	technique	NOUN
fcis-7982	95	13	to	to	PART
fcis-7982	95	14	find	find	VERB
fcis-7982	95	15	scoring	scoring	NOUN
fcis-7982	95	16	functions	function	NOUN
fcis-7982	95	17	for	for	ADP
fcis-7982	95	18	knowledge	knowledge	NOUN
fcis-7982	95	19	graph	graph	NOUN
fcis-7982	95	20	tasks	task	NOUN
fcis-7982	95	21	,	,	PUNCT
fcis-7982	95	22	and	and	CCONJ
fcis-7982	95	23	in	in	ADP
fcis-7982	95	24	the	the	DET
fcis-7982	95	25	future	future	NOUN
fcis-7982	95	26	,	,	PUNCT
fcis-7982	95	27	if	if	SCONJ
fcis-7982	95	28	we	we	PRON
fcis-7982	95	29	can	can	AUX
fcis-7982	95	30	combine	combine	VERB
fcis-7982	95	31	the	the	DET
fcis-7982	95	32	searched	search	VERB
fcis-7982	95	33	neural	neural	ADJ
fcis-7982	95	34	networks	network	NOUN
fcis-7982	95	35	with	with	ADP
fcis-7982	95	36	the	the	DET
fcis-7982	95	37	searched	search	VERB
fcis-7982	95	38	scoring	scoring	NOUN
fcis-7982	95	39	functions	function	NOUN
fcis-7982	95	40	,	,	PUNCT
fcis-7982	95	41	we	we	PRON
fcis-7982	95	42	believe	believe	VERB
fcis-7982	95	43	that	that	SCONJ
fcis-7982	95	44	we	we	PRON
fcis-7982	95	45	can	can	AUX
fcis-7982	95	46	not	not	PART
fcis-7982	95	47	only	only	ADV
fcis-7982	95	48	solve	solve	VERB
fcis-7982	95	49	the	the	DET
fcis-7982	95	50	tasks	task	NOUN
fcis-7982	95	51	in	in	ADP
fcis-7982	95	52	knowledge	knowledge	NOUN
fcis-7982	95	53	graphs	graph	NOUN
fcis-7982	95	54	better	well	ADV
fcis-7982	95	55	,	,	PUNCT
fcis-7982	95	56	but	but	CCONJ
fcis-7982	95	57	also	also	ADV
fcis-7982	95	58	improve	improve	VERB
fcis-7982	95	59	the	the	DET
fcis-7982	95	60	automation	automation	NOUN
fcis-7982	95	61	to	to	ADP
fcis-7982	95	62	a	a	DET
fcis-7982	95	63	great	great	ADJ
fcis-7982	95	64	extent	extent	NOUN
fcis-7982	95	65	.	.	PUNCT
fcis-7982	96	1	most	most	ADJ
fcis-7982	96	2	previous	previous	ADJ
fcis-7982	96	3	studies	study	NOUN
fcis-7982	96	4	on	on	ADP
fcis-7982	96	5	knowledge	knowledge	NOUN
fcis-7982	96	6	graph	graph	NOUN
fcis-7982	96	7	embedding	embed	VERB
fcis-7982	96	8	learning	learning	NOUN
fcis-7982	96	9	have	have	AUX
fcis-7982	96	10	focused	focus	VERB
fcis-7982	96	11	on	on	ADP
fcis-7982	96	12	triad	triad	NOUN
fcis-7982	96	13	-	-	PUNCT
fcis-7982	96	14	based	base	VERB
fcis-7982	96	15	models	model	NOUN
fcis-7982	96	16	,	,	PUNCT
fcis-7982	96	17	in	in	ADP
fcis-7982	96	18	this	this	DET
fcis-7982	96	19	paper	paper	NOUN
fcis-7982	96	20	we	we	PRON
fcis-7982	96	21	emphasize	emphasize	VERB
fcis-7982	96	22	the	the	DET
fcis-7982	96	23	use	use	NOUN
fcis-7982	96	24	of	of	ADP
fcis-7982	96	25	relational	relational	ADJ
fcis-7982	96	26	paths	path	NOUN
fcis-7982	96	27	to	to	PART
fcis-7982	96	28	learn	learn	VERB
fcis-7982	96	29	from	from	ADP
fcis-7982	96	30	knowledge	knowledge	NOUN
fcis-7982	96	31	graphs	graph	NOUN
fcis-7982	96	32	,	,	PUNCT
fcis-7982	96	33	using	use	VERB
fcis-7982	96	34	neural	neural	ADJ
fcis-7982	96	35	networks	network	NOUN
fcis-7982	96	36	to	to	PART
fcis-7982	96	37	balance	balance	VERB
fcis-7982	96	38	short	short	ADJ
fcis-7982	96	39	-	-	PUNCT
fcis-7982	96	40	term	term	NOUN
fcis-7982	96	41	and	and	CCONJ
fcis-7982	96	42	long	long	ADJ
fcis-7982	96	43	-	-	PUNCT
fcis-7982	96	44	term	term	NOUN
fcis-7982	96	45	information	information	NOUN
fcis-7982	96	46	in	in	ADP
fcis-7982	96	47	the	the	DET
fcis-7982	96	48	paths	path	NOUN
fcis-7982	96	49	,	,	PUNCT
fcis-7982	96	50	and	and	CCONJ
fcis-7982	96	51	if	if	SCONJ
fcis-7982	96	52	this	this	DET
fcis-7982	96	53	approach	approach	NOUN
fcis-7982	96	54	is	be	AUX
fcis-7982	96	55	applied	apply	VERB
fcis-7982	96	56	to	to	ADP
fcis-7982	96	57	inference	inference	NOUN
fcis-7982	96	58	tasks	task	NOUN
fcis-7982	96	59	of	of	ADP
fcis-7982	96	60	knowledge	knowledge	NOUN
fcis-7982	96	61	graphs	graph	NOUN
fcis-7982	96	62	it	it	PRON
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fcis-7982	96	65	that	that	SCONJ
fcis-7982	96	66	it	it	PRON
fcis-7982	96	67	will	will	AUX
fcis-7982	96	68	also	also	ADV
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fcis-7982	96	70	well	well	ADV
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fcis-7982	97	4	]	]	X
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fcis-7982	98	11	pattern	pattern	NOUN
fcis-7982	98	12	recognition[c	recognition[c	PROPN
fcis-7982	98	13	]	]	PUNCT
fcis-7982	98	14	,	,	PUNCT
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fcis-7982	98	17	computer	computer	NOUN
fcis-7982	98	18	vision	vision	NOUN
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fcis-7982	98	25	:	:	PUNCT
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fcis-7982	100	4	:	:	PUNCT
fcis-7982	100	5	a	a	DET
fcis-7982	100	6	survey[j	survey[j	NOUN
fcis-7982	100	7	]	]	PUNCT
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fcis-7982	101	8	20	20	NUM
fcis-7982	101	9	:	:	PUNCT
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fcis-7982	103	13	.	.	PUNCT
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fcis-7982	105	1	[	[	X
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fcis-7982	110	6	a	a	DET
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fcis-7982	116	6	systems[c	systems[c	PROPN
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