13 Vol. 23 No. 1, April 2023, pp. 13 – 24 DOI: 10.24071/joll.v23i1.4967 Available at https://e-journal.usd.ac.id/index.php/JOLL/index This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Databases on the Indonesian Prefixes PE- and PEN- Karlina Denistia karlinadenistia@staff.uns.ac.id English Diploma Program, Vocational School, Universitas Sebelas Maret, INDONESIA Abstract Article information This paper provides the theoretical grounding in constituting databases related to PE- and PEN-, two Indonesian nominalizing prefixes, which have various meanings (e.g., patient, agent, or instrument). The first database contains the words with PE- and PEN- whereas the second database provides the cosine similarity between two words of interest. Using a written Indonesian corpus as the primary source (Leipzig Corpora Collection), the databases contain the following information: PE- or PEN- prefixes, allomorph of PEN-, base word, semantics role, morphological variation, cosine similarity, as well as the word frequency. Furthermore, this paper elaborates the theoretical consideration on how each information was cultivated. In building the databases, Indonesian morphological parser and Word to Vector were used to analyze the Indonesian morphological status and to put the words in the corpus into a vector. In addition, manual verification for the data against the Indonesian comprehensive dictionary was also conducted. In the end, the databases are available for free so that the data could be used as materials for a corpus-based analysis on Indonesian morphology. This research shed light to a careful and thorough classification of the open-access databases of PE- and PEN- from their allomorphs, base word, semantics role, and morphological variation. The information provided in this article is hoped to be contributive in Indonesian morphology specifically, and other linguistics fields (e.g., corpus linguistics and quantitative linguistics) in general. Keywords: corpus data; morphology; prefixes; cosine similarity Received: 5 May 2022 Revised: 25 November 2022 Accepted: 3 December 2022 Introduction PEN- and PE- are two nominalizing prefixes to create an agent, an instrument, or a patient. Several studies related to the prefixes’ form, meaning and their corresponding verbs have been conducted to investigate PEN- and PE- (Dardjowidjojo, 1983; Ramlan, 1985; Chaer, 2008; Putrayasa, 2008; Sneddon et al., 2010; Subroto, 2012; Ermanto, 2016; Sugerman, 2016). PEN-, the first prefix, derives https://e-journal.usd.ac.id/index.php/JOLL/index Journal of Language and Literature ISSN: 1410-5691 (print); 2580-5878 (online) Karlina Denistia 14 nouns from a process of affix substitution with MEN- verbal prefix (e.g., pembaca ‘writer’- membaca ‘to read’). PE-, the second prefix, derives nouns from a process of affix substitution with ber- or di- verbal prefixes (e.g., pelari ‘runner’-berlari ‘to run’ and pesapa ‘addressee’-disapa ‘to be addressed’). From the semantics perspective, both forms might occur in a similar semantics role (Sneddon et al., 2010). PEN- expresses agent, instrument, or causer. For instance, from the base word kasih ‘to love’ an agent pengasih ‘lover’ is derived, pemotong ‘cutter’ is derived from potong ‘to cut’, as well as from the base word sakit ‘to be sick’ becomes a causer penyakit ‘disease’. Words with PE-, meanwhile, express patient, agent, or instrument (e.g., sapa ‘to address’-pesapa ‘addressee’, lari ‘to run’-pelari `runner’, pekasih ‘love poison). Nasalization in PEN-, denoted by ‘N’, shows that it has five nasalized allomorphs (e.g., PENpen-, PENpem-, PENpeng-, PENpeny-, PENpenge-). There is only one allomorph that does not follow the nasalization rule, PENpe-, which is described as very similar to the invariant PE-. As a result, non-native Indonesian may find difficulty to differentiate PE- and PEN- as one of PEN- allomorph occasionally appears in the same phonological environment (see Table 1). For example, pelari ‘runner’ is PE-, whereas pelukis ‘painter’ is PEN- although both proceed a stem initialized by the lateral liquid /l/. The only way to differentiate PEN- and PE- in this circumstance is by relating them to the corresponding verb. The overlapping issue on these two prefixes is not yet well addressed until now. What makes it more difficult to distinguish PE- and PEN- is because there has not been a consensus whether these formations are derived from one or two prefixes (Denistia, 2018). What might be the reason of this inconclusive finding of PE- and PEN- is due to a few numbers of observations. Therefore, a set of databases are needed to explore this phenomenon from the quantitative perspective. Table 1. Words with PE- and PEN- that have similar phonological condition Word Prefix Noun Translation PEN- Allomorph Base Word Base Translation Base Word Class Semantic Role pelari PE- runner lari to run v agent pelukis PEN- painter pe lukis to paint v agent pemusik PE- musician musik music n agent pemasak PEN- cooker pe masak to cook v instrument perenang PE- swimmer renang to swim v agent perokok PEN- smoker pe rokok cigarette n agent pewisata PE- traveler wisata to travel v agent pewawancara PEN- interviewer pe wawancara interview n agent Recent studies on these prefixes conducted analyses based on corpus data (Denistia & Baayen, 2019, 2022a, 2022b, Denistia et al., 2022). Their research focused on investigating whether PE- and PEN- are allomorphs from their productivity, computational learning, and semantics distribution respectively. One of their significant findings concluded that PE- and PEN- should be treated as two different prefixes due to their different productivity and semantics. PEN- is found more productive than PE-. In addition, although both PE- and PEN- creates agents; PEN- is productive in creating instruments, while PE- is productive in creating patients. Moreover, the number of derived words with PEN- (and all of its allomorphs) is linearly dependent on the number of base words for MEN- allomorphs. PE-, however, is an outlier in the linearity of the base words’ productivity. Apart from productivity analysis, using semantics Journal of Language and Literature Vol. 23 No. 1 – April 2023 ISSN: 1410-5691 (print); 2580-5878 (online) 15 distribution (Mikolov et al., 2013), Denistia et al. (2022) measured the similarity of all possible combination between PE- and PEN-. They found that PE- and PEN- are semantically discriminable. PE- and PEN- cosine similarity is significantly different only across prefixes. Furthermore, compared to derived words with PEN-, words starting with PE- have meanings that are more similar to their noun bases. This paper provides a detailed explanation of the materials and database used in Denistia & Baayen (2019) and Denistia et al. (2022). Theoretical grounding on how the information in database were classified (e.g., the classification of PE- and PEN-, allomorph of PEN-, semantics role, cosine similarity, tokens frequency in the corpus) is described. The tools used to generate two database of PE- and PEN- are also elaborated in this paper. The information and explanation provided in this paper are structured in a way that I hope to be generally contributive in both corpus and quantitative linguistics analysis. In what follows, I first introduce the main corpus and tools. In the next section, I present the databases. Finally, I conclude the study in the final section. Along with this paper, two databases are made available for public and can be downloaded at http://bit.ly/PePeNProductivity and http://bit.ly/PePeNSemVector. Methodology Leipzig Corpora Collection The Leipzig Corpora Collection corpus, which includes a range of Indonesian textual registers from 2008 to 2012, including newspapers, the web, and Wikipedia (Goldhahn et al., 2012), was used to create the PePeN Database. This corpus contains 36.608.669 word-tokens that belong to 112.025 different word types and appear in 2.759.800 sentences. Started by the Projekt Deutscher Wortschatz since 15 years ago, now, the Leipzig Corpora Collection has developed into 136 monolingual corpora including Indonesian (Goldhahn et al., 2012; Quasthoff et al., 2006). It uses available online newspapers to crawl as a method for gathering text data [http://www.abyznewslinks.com]. In addition, it uses a framework for parallel Web crawling utilizing http://www.httrack.com as the Web site copier. Another way that was conducted to collect the corpus is by crawling the World Wide Web randomly, utilizing FindLinks [http://wortschatz.uni- leipzig.de/findlinks/] (Heyer & Quasthoff, 2004). Besides, UDHR [http://www.ohchr.org] and Wikipedia [http://sourceforge.net/projects/wikiprep/] were also used as its resource, resulting in more texts in various languages that are covered for this corpora. The text data in the corpora has been preprocessed using the HTML-Stripping in order to take the data containing the well-formed sentences, LangSepa created by Pollmächer (2011) so that each language would be clustered separately, and www.sonderzeichen.de to generate the sentence boundary. To sidestep the copyright issue and to make it impossible to recreate the original material, the phrases were jumbled. The Indonesian Leipzig Corpora Collection corpus is made available online at https://corpora.uni- leipzig.de/en?corpusId=ind_mixed_2013. Indonesian Morphological Parser (MorphInd) The MorphInd parser (Larasati et al., 2011), which has an overall accuracy of 84.6%, was used to perform morphological analysis on the words in the PePeN Database. It was run in non-compound mode. Before starting the parser, I manually fixed 200 words beginning with PE- or PEN- that had typos (see Table 2 for illustrations) and added the frequency of the typos to the frequency of the words. Additionally, using the dictionary as the gold standard manual verification, MorphInd's recall for detecting PE- and PEN- was 0.82 and its precision for doing so was 0.98. The R open-source programming language, version 3.3.3, was used to process the data in R Studio(R Team, 2015). R is an open source that can be downloaded at https://cran.r-project.org for free (available for Windows, Mac, and Linux users). http://bit.ly/PePeNProductivity http://bit.ly/PePeNSemVector http://www.abyznewslinks.com/ http://www.httrack.com/ http://wortschatz.uni-leipzig.de/findlinks/ http://wortschatz.uni-leipzig.de/findlinks/ http://www.ohchr.org/ http://sourceforge.net/projects/wikiprep/ https://corpora.uni-leipzig.de/en?corpusId=ind_mixed_2013. https://corpora.uni-leipzig.de/en?corpusId=ind_mixed_2013. https://cran.r-project.org/ Journal of Language and Literature ISSN: 1410-5691 (print); 2580-5878 (online) Karlina Denistia 16 Table 2. Typo example entries in the database Word Translation Frequency Typo Revision Freq of Typo pelukis painter 321 pelunis 1 pemusik musician 208 pemuzik 7 penulis writer 5312 pemnulis,pemulis,pengnulis,penulia, penulih,penulsi,penults,penulus,peulis 1,1,1,1, 1,1,1,1,1 perokok smoker 671 peerokok,peroko,perokor 1,1,1 Table 3. The MorphInd parser output examples Word Parser Noun Translation Allomorph Base Base Translation pencipta peN+cipta_NSD creator pen cipta to create pendaki peN+daki_NSD climber pen daki climbing peninju peN+tinju_NSD puncher pen tinju punch petinju peN+tinju_NSD boxer tinju boxing petani petani_NSD rice farmer tani farming peternak peternak_X– farmer ternak cattle pengelas peN+kelas_NSD welder penge las to weld pengusut peN+kusut_NSD investigator peng usut to investigate Table 3 shows the sample output of MorphInd parser. From Table 3, one can see that MorphInd correctly parses pencipta, pendaki, and peninju. However, MorphInd parser is not accurate in identifying PE- in petinju, petani, and peternak. In several instances, MorphInd is unable to accurately detect single-syllable base words. Pengelas ‘welder’, for instance, MorphInd identifies the base word is kelas ‘classroom’, thus the morphological process is [PENpeng- + kelas]. The base word of pengelas ‘welder’ is las ‘weld’ and thus the morphological analysis is [PENpenge- + las]. Also, the base identified by the parser is not accurate as in pengusut ‘investigator’. Pengusut ‘investigator’ is supposedly formed from the base word usut ‘to investigate’, but MorphInd identifies its base as kusut ‘tangled’. Thus, the correct parsing is [PENpeng- + usut] and not [PENpeng- + kusut]. Due to some misidentification, the online version of Kamus Besar Bahasa Indonesia, a comprehensive dictionary of Indonesian, (http://kbbi.kemdikbud.go.id; viewed on June 2016), which was published in 2012, and comprises more than 90,000 lemmas, was used to manually examine and correct MorphInd output as needed (Alwi, 2012). Word to Vector I lemmatized the Leipzig Corpora Collection corpus based on MorphInd’s morphological analyses output. Prior to the lemmatization, all the word in the corpus were lower-cased, numbers were excluded, punctuation marks and 15 highest frequency stop words were removed. I removed stop words itu ‘that’, ini ‘this, dan ‘and’, yang ‘which’, pada ‘of’, di ‘in’, dengan ‘with’, akan ‘will’, juga ‘also’, dari ‘from’, untuk ‘to/for’, dalam ‘inside’, ke ‘to’, karena ‘because’, and tidak ‘not’. MorphInd lemmatizes anti-, pra-, pasca-, non-, ku- ‘I’, -ku ‘my’, kau- ‘you’, -mu ‘your’, -nya ‘his/her/its’, se- ‘one’, per- ‘per’, and particles (e.g. -lah to show emphasize, -kah to ask question) as bound morphemes. The suffix -nya was marked to indicate its function as a question word by nya-WH. However, antar was not separated from its base because it has a different reading when this word occurs in a form of a simple word (e.g., antar paket itu ‘pick that package up’ versus antaragama ‘among religions`). Finally, hyphenated words http://kbbi.kemdikbud.go.id/ Journal of Language and Literature Vol. 23 No. 1 – April 2023 ISSN: 1410-5691 (print); 2580-5878 (online) 17 were kept in the form of reduplication as the way they are (e.g., iteration, intensification, or plurality; Rafferty (2002), Chaer (2008), Dalrymple & Mofu (2012), Sugerman (2016)). Word to Vector was made used to convert all the lemmatized words in the corpus into a vector. Each word in the corpus was encapsulated in high-dimensional vectors so that a vector will represent a word (Turney & Pantel (2010)). Cosine similarity, which is length-normalized and is equal to the inner product of the vectors, was used to calculate the degree of semantic similarity between two lemmas, based on the distributional information of the words (their co- occurrences with other words in huge corpora). The similarity of the cosine of the angle 𝜃 is cosine similarity between �⃗⃗� and �⃗⃗⃗⃗� . In the PePeN CosSim Database, the results of computing the cosine similarity value for each conceivable pair combination of words from the set of PE-, PEN-, and their base words were stored. Lemma1, Lemma2, Cosine similarity (the cosine similarity value between Lemma 1 and Lemma 2), and Derived-Base Cosine Similarity (cosine similarity measure of the derived word with its base word) are all included in the database. Finally, I collected a total of 358224 permutation of derived words with PEN- and 59810 permutations of derived words with PE- together with their cosine similarity to their base words (see Table 4 for list of example entries of this database). Words with a token frequency less than 5 were not included in this database. Table 4. PePeN CosSim Database’s examples of entries Lemma1 L1 English Lemma 2 L2 English CosSim L1L2 Prefix L1 Prefix L2 Base L1 B1 English Base L2 B2 English Cossim L1-B1 Cossim L2-B2 pencipta creator pelatih trainer 0.022 peN peN cipta to create latih to train 0.358 0.192 pencipta creator pemilih voter -0.111 peN peN cipta to create pilih to vote 0.358 0.364 pencipta creator pencari seeker 0.092 peN peN cipta to create cari to search 0.358 0.147 peternak farmer pengupas peeler -0.03 pe peN ternak to farm kupas to peel 0.717 0.212 peternak farmer penyapu sweeper 0.03 pe peN ternak to farm sapu broom 0.717 0.374 peternak farmer penyemprot sprayer 0.005 pe peN ternak to farm semprot to spray 0.717 0.646 Results and Discussion PePeN Database includes a total of 3090 words; 2818 words with PEN-, 267 words with PE-, and 4 words with the unproductive variant PER-, Benjamin (2009). The latest prefix is not discussed in this paper. For the sake of the quantitative analysis, both PePeN Database and PePeN CosSim Database provide the information on how many times the words with PE- or PEN- and their base words occur in the corpus; usually called as ‘token frequency’ (see Table 5). The mentioned frequencies are the word's overall frequency and are not segmented by meaning. Journal of Language and Literature ISSN: 1410-5691 (print); 2580-5878 (online) Karlina Denistia 18 Table 5. Sample entries of PePeN Database Noun Word Noun Translati on Frequen cy PE - Allomo rph Base Word Base Translati on Base Word Class Base Frequency Semantic Role pelari runner 358 T lari to run v 2312 agent pelukis painter 321 F pe lukis to paint v 282 agent pemasak cooker 6 F pe masak to cook v 1070 instrument pemusik musician 208 T musik music n 9799 agent perenang swimmer 296 T renang to swim v 821 agent perokok smoker 671 F pe rokok cigarette n 3619 agent pewawanc ara interview er 101 F pe wawanca ra interview n 3015 agent pewisata traveler 1 T wisata to travel v 7371 agent Classifying PE- and PEN- There are two ways to differentiate PE- and PEN-. The first one is by applying the phonological condition on PEN- and its six allomorphs: PENpen-, PENpeng-, PENpem-, PENpeny-, PENpe-, and PENpenge-. The phonological context influences the nasal allomorphy of PEN-. The phonological conditioning of PEN- allomorphs is summarized by Ramlan (1985), Sugerman (2016), and Sukarno (2017) as follows: 1. -N is lost with base words initialized by /ny/, /w/, /r/, /m/, /n/, /ng/, or /l/ a. peN- + nyanyi ‘to sing’ to be penyanyi ‘singer’ b. peN- + wangi ‘good smell’ to be pewangi ‘instrument to give a good smell’ c. peN- + rusak ‘broken’ to be perusak ‘destroyer’ d. peN- + mabuk ‘drunk’ to be pemabuk ‘who gets drunk’ e. peN- + lukis ‘to paint’ to be pelukis ‘painter’ 2. -N becomes -n with base words initialized by /t/, /d/, /j/, /c/, /sy/, or /z/ a. peN- + tulis ‘to write’ to be penulis ‘writer’ b. peN- + daki ‘to climb’ to be pendaki ‘climber’ c. peN- + jelajah ‘to explore’ to be penjelajah ‘explorer’ d. peN- + cuci ‘to wash’ to be pencuci ‘instrument to wash/agent who wash’ 3. -N becomes -ng with base words initialized by a vowel or /k/, /h/, /g/, or /kh/ a. peN- + ingat ‘to remember’ to be pengingat ‘reminder’ b. peN- + ganti ‘replacement’ to be pengganti ‘who/which replaces’ c. peN- + halang ‘block’ to be penghalang ‘barrier’ d. peN- + kuasa ‘power’ to be penguasa ‘ruler’ 4. -N becomes -m with base words initialized by /p/, /b/, or /f/ a. peN- + buat ‘to make’ to be pembuat ‘maker’ b. peN- + picu ‘trigger’ to be pemicu ‘trigger’ c. peN- + fitnah ‘to sander’ to be pemfitnah ‘slander’ 5. -N becomes -ny with base words initialized by /s/ a. peN- + saring ‘to filter’ to be penyaring ‘who filters’ 6. penge- occurs in monosyllabic base words a. peN- + cek ‘to check’ to be pengecek ‘checker’ There are some exceptions of these phonological condition given by Sneddon et al. (2010). If the stem is borrowed from other languages, some bases with initial /k/, /s/, /t/, /p/ are not lost. Thus, the derived words as a result of borrowing becomes more accepted as an Indonesian word as in the stem klasifikasi ‘classification’ to be pengklasifikasi ‘classifier’. Table 6 shows the second way to distinguish PE- and PEN-, which is by process Journal of Language and Literature Vol. 23 No. 1 – April 2023 ISSN: 1410-5691 (print); 2580-5878 (online) 19 of affix substitution. In this case, the prefix PEN- changes verbs with the MEN- prefix into noun. MEN- also has 6 allomorphs (MENmeng- , MENmen-, MENmem-, MENme-, MENmeny-, and MENmenge-). Again by affix substitution, the prefix PE- creates nouns from verbs with the prefix BER- (Dardjowidjojo, 1983; Ramlan, 1985; Putrayasa, 2008; Benjamin, 2009; Sneddon et al., 2010; Tjia, 2015; Ermanto, 2016). However, it should be noted that Ramlan (1985) acknowledged only several verbs with BER- correlates to PE-. Table 6. Examples of the corresponding PEN- with MEN- and PE- with BER-. Noun Word Noun Translation PE- Base Word Base Translation Corresponding Verb Verb Translation pelari runner TRUE lari to run berlari to run pelukis painter FALSE lukis to paint melukis to paint pemusik musician TRUE musik music bermusik to play music pemasak cooker FALSE masak to cook memasak to cook perenang swimmer TRUE renang to swim berenang to swim perokok smoker FALSE rokok cigarette merokok to smoke pewisata traveler TRUE wisata to travel berwisata to travel pewawancara interviewer FALSE wawancara interview mewawancarai to interview The base words for both the verbs with MEN- or BER- and their nominalizations with PEN- and PE- can be nouns, adjectives, and verbs. Verbs with MEN-, which ordinarily renders a transitive verb, can be added by -i and -kan suffixes. The suffixes -i and -kan typically signify intensification or iteration while also adding a location, a beneficiary, or a causer as a new argument (Arka et al., 2009; Kroeger, 2007; Sneddon et al., 2010; Sutanto, 2002; Tomasowa, 2007). In the same vein, verbs with BER-, which has infrequent allomorphs be- and bel-, essentially express reciprocity, stativity, or reflexivity. BER- are found with -an or -kan, but PE- does not combine with the suffixes (Chaer, 2008; Kridalaksana, 2007; Putrayasa, 2008; Ramlan, 1985; Sneddon et al., 2010). The verb structure with BER-an and BER-kan create respectively reciprocative (e.g., peluk ‘to hug’-berpelukan ‘to hug each other’) or ‘having X’ (e.g., dasar ‘base’-berdasarkan ‘based on') (Sneddon et al., 2010). Although derived nouns with MEN- can be further modified with the suffixes -i or -kan, derived nouns with PEN- do not. Nevertheless, the verbs with MEN-/-i or MEN-/-kan affixes may have semantics that are similar to the derived nouns. For instance, pewawancara, ‘interviewer’, is related to mewawancarai ‘to interview someone’. Also, although the corresponding verbs with BER- can be extended by -an or -kan suffixes, derived nouns with PE- do not carry the suffixes. Base Word of PE- and PEN- Indonesian nouns, verbs, and adjectives can be monomorphemic or polymorphemic. Kridalaksana (2007) explained that nouns are classified into abstract or concrete, animate or inanimate, countable or uncountable, as well as collective or non-collective. In term of verbs, they can be characterized by adding dengan and adjective which function as an adverbial of manner (referring to the -ly suffix in English). For instance, berlari ‘to run’ can be modified into berlari dengan cepat ‘to run fast’; therefore, berlari is a verb. Verb formations are classified into transitive or intransitive, active or passive or anti-active or anti-passive, reciprocal or nonreciprocal, reflective or nonreflective, copulative or equative, and performative or constant. With regards to adjectives, they could be indicated by tidak ‘not’ as the negation, premodifiers (e.g., sangat ‘very’, agak ‘pretty’, lebih ‘more’), and that they could modify nouns. They are classified into predicative or attributive and gradual or nongradual adjectives. Journal of Language and Literature ISSN: 1410-5691 (print); 2580-5878 (online) Karlina Denistia 20 Table 7 shows examples of the base word and base word category in the database. In PePeN Database and PePeN CosSim Database, the dictionary and MorphInd were used to decide what base word category of the PE- and PEN- nouns. There might be a conflict in determining the base word category between those two tools. Upon that case, I followed the base word category information provided by the Indonesian dictionary. However, in the case where the information on the word category of the base is not provided in the dictionary, I used the MorphInd parser identification. I did not provide a further classification on each type (such as whether the verb is transitive or intransitive, or whether the noun is animate or inanimate). Table 7. Examples of PePeN base word and base word category. Word Noun Translation PE- Allomorph Base Word Base Translation Base Word Class pencipta creator F pen cipta to create n pendaki climber F pen daki climbing v peninju puncher F pen tinju punch n petinju boxer T tinju boxing n petani rice farmer T tani farming n peternak farmer T ternak cattle n pengelas welder F penge las to weld n pengusut investigator F peng usut to investigate v Semantics Role of PE- and PEN- Manual verification of all PE- and PEN- words was not doable. Therefore, I did a manual annotation for the semantic role for all derived words with PE- and PEN- and checked against the usage in the corpus for at least one token, as well as the dictionary (Alwi, 2012). One of the implications of this limitation is that the ambiguity in assigning a semantic role to PE- and PEN- words which express multiple semantic roles could not be resolved. Thus, it is possible that there are cases for which a semantic role was realized in the corpus with no semantic role registered in the database. Table 8 shows various readings for PE- and PEN- formations. As in English, -er nominalizations may have a range of semantic roles (e.g., printer, which has both an instrument and agent reading) (G. Booij, 2010; G. Booij & Lieber, 2004). I did not distinguish between impersonal agent in this research. The term impersonal agent was introduced by Booij (1986) for ‘radio station’ of the Dutch word zender which also has both an instrumental interpretation, ‘transmitter’, and an agentive meaning, ‘one who sends’. Although it is commonly known that PEN- create agents, patients, and instruments (Sneddon et al., 2010), the database contains a small number of instances of causer (e.g., penyakit ‘disease’) and location (e.g., penghujung ‘the end’). Semantic roles that are not registered in the database may nonetheless be used in the corpus, which is plausible and perhaps likely. Journal of Language and Literature Vol. 23 No. 1 – April 2023 ISSN: 1410-5691 (print); 2580-5878 (online) 21 Table 8. Examples of PePeN semantic role. No Word Noun Translation PE- Base Word Base Translation Semantic Role 1 pembanding who compares F banding to compare agent 2 pembanding something to compare F banding to compare instrument 3 pembanding something to be compared F banding to compare patient 4 pesiar cruise T siar to broadcast instrument 5 pesiar traveler T siar to broadcast agent 6 penyiar radio announcer F siar to broadcast agent 7 penyelam who dives F selam to dive agent 8 peselam diver (athlete) T selam to dive agent 9 pengasih who loves F kasih love agent 10 pekasih love poison T kasih love instrument 11 penyakit disease F sakit to be sick causer 12 pesakit patient T sakit to be sick patient 13 penyapa addressor F sapa to address agent 14 pesapa addressee T sapa to address patient Words with more than one semantic role have multiple entries in the database, one row per role (cf. Table 8, rows 1-6). Occasionally do the prefixes PEN- and PE- attach to the same base word; often, the form with PE- alludes to a profession in a semantic sense, whereas the word with PEN- does not (cf. Table 8, rows 7 and 8). In some instances, the form with the prefix PEN- expresses the agent, causer, or instrument, while the form with the prefix PE- expresses the patient or agent (cf. Table 8, rows 9-14). Morphological Variation of PE- and PEN- In Indonesian, there are bound morphs for possession of nouns, (first -ku, second -mu, and third person singular -nya), subject (first ku- and second person singular kau-) and object (first -ku, second -mu, and third person singular -nya) marking on verbs (Sneddon et al., 2010). These bound morphemes fulfill the contextual inflection, an inflection which is not dictated by syntax, proposed by Booij (1996). Additionally, there are two suffixes that can be added to verbs or nouns to indicate emphasize (-lah) or query (-kah). Clitics are the term given to bound morphemes, which are phonologically condensed versions of free pronouns (Kridalaksana, 2008). Therefore, I will refer to these morphs as inflectional because they alter existing words rather than creating new ones, much to how English adverbs modify verbs. Reduplication creates different semantic functions on verbs and adjectives, including intensification and iteration respectively, as well as to convey the plural for nouns. (Rafferty, 2002; Chaer, 2008; Dalrymple & Mofu, 2012; Sugerman, 2016). According to Booij (1996), reduplication as well as -lah, -kah and -pun instantiate inherent inflection. Although it may have syntactic relevance, inherent inflection is the kind of inflection that is not required by the syntactic context. In the database, reduplication is more like syntactic modification than to word formation. Hence, reduplicated forms were classified as inflectional because their semantics are still related to a plurality (e.g., intensifier or iterative). Some examples on the inflection are listed in Table 9. Journal of Language and Literature ISSN: 1410-5691 (print); 2580-5878 (online) Karlina Denistia 22 Table 9. Examples of inflection in PePeN database. Word Translation PE- Allomorph Base Word Base Word Class Inflection pemerintahnya his/her/its government F pem perintah n Possession pemerintahlah government (emphasize) F pem perintah n Particle pemerintahpun government (emphasize) F pem perintah n Particle pemerintah- pemerintah government (plural) F pem perintah n Reduplication pelarinya runners T lari v Possession pelari-pelari his/her/its runner T lari v Reduplication Conclusion Given the fact that there have been many qualitative descriptive about the Indonesian PE- and PEN- prefixes, some questions on how to discriminate them remain unanswered. PEN- has 5 allomorphs: PENpen-, PENpem-, PENpeng-, PENpeny-, PENpenge- that follow the nasalization rule and there is only one allomorph, PENpe-, that is not nasalized. A case arises when these two are in a contest, appearing in the same phonological environment. Moreover, there has been an inconclusive agreement among theories whether these nominalizing prefixes are one or two independent formations. This paper provides detailed information on two databases, namely PePeN Database and PePeN CosSim Database, as the contribution to a quantitative approach for Indonesian linguistics. Taken from Leipzig Corpora Collection, I used several tools and programming language to classify the database from its prefix, allomorph, base word, base word class, semantics role, inflection, as well as cosine similarity. These databases could be used to conduct a further study on PE- and PEN- formations. This study, however, is limited to only two nominalizing prefixes, PE- and PEN-. Indonesian has other nominalizing affixes (e.g., -an as in luar `outside’ to luaran `outcome’, Makmur `prosperous’ to ke-/-an as in kemakmuran `prosperity’). In addition, PEN- could also attach to the suffix -an to form peN- /-an circumfixes (e.g., tinggal `stay’ to peninggalan `heritance’). Another noun could also be derived from per-/-an, such as unbah `to change’ to perubahan `a change’. Therfore, some explanation on databases of other nominalizing affixes would be useful for further research. Acknowledgment Lembaga Pengelola Dana Pendidikan, the endowment fund for education in Indonesia, provided funding for this study under grant number PRJ-1610/LPDP/2015. References Alwi, H. (2012). Kamus Besar Bahasa Indonesia (fourth). Jakarta: Gramedia Pustaka Utama. Arka, I. W., Dalrymple, M., Mistica, M., & Mofu, S. (2009). A linguistic and computational morphosyntactic analysis for the applicative -i in Indonesian. In M. Butt & T. H. 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