SEMI-AUTOMATIC ELIMINATION OF LEXICAL AMBIGUITIES IN MODERN GREEK BY USING THE ELAG SYSTEM

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1 SEMI-AUTOMATIC ELIMINATION OF LEXICAL AMBIGUITIES IN MODERN GREEK BY USING THE ELAG SYSTEM KYRIAKI IOANNIDOU ARISTOTLE UNIVERSITY OF THESSALONIKI Περίληψη Αντικείµενο της παρούσας έρευνας είναι η ηµι-αυτόµατη εξάλειψη λεξικών αµφισηµιών µέσω τυποποιηµένων γραµµατικών που εφαρµόζονται σε ελληνικά ηλεκτρονικά σώµατα κειµένων. Η µελέτη αυτή γίνεται στα πλαίσια ερευνών για την αυτόµατη ανάλυση της Νέας Ελληνικής που διεξάγει η Μονάδα Αυτόµατης Επεξεργασίας Φυσικών Γλωσσών του Εργαστηρίου Μετάφρασης και Επεξεργασίας του Λόγου του Α.Π.Θ. Σε αυτό το στάδιο, οι αµφισηµίες που εξετάζονται αφορούν κυρίως σε ουσιαστικά και επίθετα µε κοινούς τύπους στις διάφορες πτώσεις του ενικού και/ή του πληθυντικού αριθµού, καθώς και σε λέξεις διαφορετικών γραµµατικών κατηγοριών. Το πρόγραµµα που χρησιµοποιήθηκε για την ηµι-αυτόµατη εξάλειψη των αµφισηµιών αυτών είναι το ELAG (Elimination of Lexical Ambiguities by Grammars), το οποίο είναι ενσωµατωµένο στο αυτόµατο σύστηµα ανάλυσης φυσικών γλωσσών UNITEX. 1. Introduction This article is a research in the field of computational linguistics and deals with eliminating ambiguities in a semi-automatic way. In Modern Greek, at the morphological level, there are two different kinds of lexical ambiguities: firstly, the same form may represent more than one different inflected forms (e.g. 1a, 1b) and secondly the same form can correspond to more than one different grammatical categories (e.g. 2a, 2b). More specifically, in the example 1a, the nominal form κλειδί corresponds to the nominative, accusative and vocative cases. In the example 1b the verbal form είναι corresponds to the third person of the present tense of the singular as well as of the plural number. In the example 2a, the form το can be a determiner or a personal pronoun, and in the example 2b, the form ήπια can be a verb, an adjective or an adverb.

2 1a. κλειδί N:Nns:Ans:Vns (key) 1 1b. είναι V:P3s:P3p (is) 2 2a. το DET+Def:Ams:Nns:Ans (the) PRO+Pers:Ans (it) 3 2b. ήπια V:J1s (drank) A:Nnp:Anp:Vnp (bland) ADV (blandly) 4 This research concerns the elimination of ambiguities among different cases of nouns and adjectives as well as ambiguities between determiners and pronouns. The disambiguation is being achieved by using the Elag programme (Elimination of Lexical Ambiguities by Grammars). After mentioning previous studies on semi-automatic ambiguity elimination and after describing how the Elag programme functions, we will describe in detail some Elag grammars created. 2. Construction of disambiguation grammars 2.1. Previous studies on disambiguation grammars Anastassiadis-Symeonidis, Kyriakopoulou, Sklavounou, Thilikos & Voskaki (2000), Sklavounou (1995), Bakoura & Voskaki (2004), Kazantzi & Voskaki (2004) and Thilikos & Voskaki (2003) have already produced studies on semi-automatical ambiguity elimination in Modern Greek. The first studies on the processed ambiguities have been conducted by Kyriacopoulou (2005) and Thilikos (2000). A semiautomatic elimination of ambiguities is based on computational linguistics rules, which are often different from the linguistics ones. Namely, linguistics rules must be transformed into computational linguistics ones with a strictly formalised structure. Such rules are applied on texts by corpus processing systems. 1 The first N stands for noun, the second N stands for nominative, A and V stand for accusative and vocative cases respectively, n stands for neuter and s for singular. 2 V stands for verb, P for present tense, 3 for third person, s for singular and p for plural. 3 DET+Def stands for definitive determiner and PRO+Pers for personal pronoun. 4 J stands for past tense, 1 for first person, A for adjective, and ADV for adverb.

3 Initially, the disambiguation rules, in terms of computational linguistics, were represented by local grammars. Local grammars are graphs that eliminate ambiguities by determining constraints in terms of context. The disadvantage of these grammars is that they are applied partially on the processed text and the applied corrections are not permanent on the text automaton. On the contrary, graphs in the Elag formalism are applied on the entire ambiguous text and the changes are kept permanently. The text automaton concerns the full morphological description of the entire text sentence per sentence. That is, for every ambiguous lemma all potential different labels are represented in detail. Thus, researchers, such as Laporte (2001), pointed out the need of creating a system that would apply a grammar to a text, in the sense that ambiguities would be actually removed. The materialisation of this idea is the Elag system, which will be presented below The Elag programme The Elag programme, inspired by E. Laporte (E. Laporte & A. Monceaux 1999) and created by O. Blanc, is integrated in the corpus processing system called Unitex 5, which was created by S. Paumier (Assistant professor, Université de Marne-la-Vallée). Unitex, when processing a text, applies electronic monolingual dictionaries 6 containing the morphological description 7 of each word. Every word may have a lot of different labels among which only one is correct in the specific context. When lexical ambiguities are to be eliminated, the text is shown in the form of a finitestate transducer called text automaton (figure 1), which allows to present ambiguities in a graphical way. 5 www-igm.univ-mlv.fr/~unitex 6 Electronic dictionaries for Modern Greek are created by the Natural Language Processing Unit of the Translation and Language Processing Laboratory of the Aristotle University of Thesssaloniki ( 7 The symbols used in examples are the ones adopted by convention by all users of Unitex for the morphological description given by the dictionaries of every language.

4 Figure 1: Text automaton (e.g. Yesterday, the minister asked for him.) As shown in figure 1, below the text, there are two windows for text automata: the first one represents the text automaton before the grammar(s) application by Elag and the second one represents the text automaton the grammar application. Elag applies one rule at a time, which can consist of a set of grammars. Figure 2 shows the formalism of an Elag grammar with no linguistic information. Figure 2: Elag grammar with no linguistic information

5 Each grammar has two rows 8 : the if part and the then part. The if part, delimited by two <!>, describes the context which must be located in order to apply the grammar. The then part, having two or, rarely, three rows and delimited by two <=>, specifies the same context in order to limit the different characterisations of a form. Different characterizations are shown in the automaton as different paths. In order to read easily an Elag grammar, we could translate the upper row as If you find the sequence X and the lower row as then, this sequence is X 1 or as then keep only the description(s) that agree(s) with the sequence X 1. All grammars that will be described in the next chapter, as well as 30% of the dictionary used in our research, are available for free on the Internet 9 when downloading Unitex, in a file called Elag. An Elag rule has certain significant advantages: firstly, an Elag rule, when applied, does not only locate the sequence described, but also interferes to the morphological analysis of the text. That is, changes are saved to the text after grammars are applied. Secondly, the applied Elag rule can consist of more than one grammars, each concerning different type of ambiguity. These grammars are applied at the same time as one united rule. Last but not least, the user can compare the linguistic analysis of the text before and after the grammar application Elag grammars This research follows a study produced last year on the creation of Elag disambiguation grammars for Modern Greek. (Blanc, Ioannidou & Voskaki 2005). Since then, research went on, grammars were applied to an extended corpus and they were enriched. In total, the grammars presented below are applied to the electronic version of the Greek newspaper TA NEA ( ), offered to us by C. Fairon (Université Catholique de Louvain) as well as to Greek corpora appeared on the Internet by 2001, offered to us by F. Guenthner (Center for Information & Language Processing, Ludwig-Maximilian Universität München). The enriched grammars we present in the next chapter concern ambiguities between determiners and pronouns and others concern the nominative, the genitive and the accusative case. 8 The manual of the Elag program was prepared by Blanc (2003). 9 www-igm.univ-mlv.fr/~unitex/download.html

6 Ambiguities between determiners and pronouns Ambiguities between determiners and pronouns may be found in the following forms: το, του, της, τον, την, τους, τις, τα. Here are some examples: 3. ΤΟ πρόγραµµα έχει ως στόχο να προβάλλει την πολιτιστική κληρονοµιά της κάθε χώρας (THE programme aims to promote the inheritance of every country 10 ) To DET+Def:Nns Του αποκάλυψε ΤΟ λόγο για τον οποίον ήρθε (He revealed to him THE reason for which he came) Το DET+Def:Ams 5. Η κοινοτική χρηµατοδοτική στήριξη µπορεί να φτάσει µέχρι το 50% των συνολικών δαπανών για ΤΟ έργο και δεν µπορεί να υπερβεί το ποσό των ECU (The Community financial support can reach (THE) 50% of the total expenses for the project and cannot exceed the ECU) Το DET+Def:Ans 6. Η κυβέρνηση ΤΟ ζήτησε (The governement asked for IT) Το PRO+Pers:Ans One way to distinguish a determiner from a pronoun is to define which parts of speech follow a determiner. Indeed, before an adjective, a noun, a numerical determiner or a number, we can have a determiner; on the contrary we cannot have a pronoun other than a personal one (e.g.7). 7. Είναι ΤΑ κορδόνια ΤΩΝ ωραίων ΤΟΥ παπουτσιών (They are THE laces of HIS nice shoes) Του PRO+Pers:Gms 10 All translations given in examples are literal translations. 11 Examples 3, 4, 5, 6 and 7 carry the correct label, which is represented after the grammar applications.

7 Thus, a grammar we have created: If you find a pronoun preceding an adjective, a noun, a numerical determiner or a number, then if it is a pronoun, it can only be a personal one. Thus, if it is not a personal pronoun, it is a determiner. In order to improve this graph, we have added the symbol V:K which represents the participle having always the syntactic functions of a noun (figure 3) (e.g. 8) 8. Είναι ο οδηγός ΤΟΥ χτυπηµένου αυτοκινήτου (He s the driver of THE crashed car) Του DET+Def:Gns Figure 3: Elag grammar eliminating ambiguities between determiners and pronouns (1) In addition to this, we have produced another graph (figure 4) completing the previous one. This graph eliminates all determiners, apart from the numerical ones when preceding a verb. According to this grammar, when the system finds either a determiner, a preposition or a pronoun before a verb in all tenses and modes (all three grammatical categories will be recognised), this form preceding the verb can only be either a pronoun or a numerical determiner. Figure 4: Elag grammar eliminating ambiguities between determiners and pronouns (2)

8 The results obtained after the application of the two grammars concerning ambiguities existing between determiners and pronouns can be seen in the following text automaton (figure 5). In particular, the form το (the) is recognized as a determiner before a noun. Figure 5: Text automaton after applying the Elag grammars concerning the ambiguities between determiners and pronouns. (e.g. The programme concerns three main actions) The nominative case Ambiguities between nominative and other cases are detected in all genders. Here are some representative examples of every genre: 9. γίγαντες N:Nmp:Amp:Vmp (giants) 10. γυναίκα N:Nfs:Afs:Vfs (woman) 11. τραπέζι Nns:Ans:Vns (table)

9 In the graph created initially concerning the nominative case, we were describing the syntax of some linking verbs (γίνοµαι: become, βαφτίζοµαι: be baptised) requiring a predicative in nominative. In the graph below, we removed these verbs, because the syntax of every verb is described in lexicon-grammars, another function of Unitex, which attributes syntactic information to words which are related to verbs 12. That is, in lexicon-grammars, the predicative of a verb is recognized and this information can be used, in the future, to eliminate ambiguities that are detected in subjects, predicatives or objects of verbs. Therefore, the nominative Elag grammar is limited to defining the nominative case of nominal groups by the article in nominative. Namely, since the masculine or the feminine article in nominative is never ambiguous, we use it to eliminate the genitive, accusative and vocative cases of the following noun, adjective etc. In order to improve the applicability percentage of the grammar created, we removed most of the if part apart from the determiner. The increase of the applicability percentage is achieved, because when there is less information in the if part, there are less constraints in the context, and as a consequence, the system locates more sequences that correspond to the if part and it applies the grammar to more sentences. More specifically, the grammar described the following: When you find a determiner in nominative and a nominal group ( if part ), the nominal group is a nominative ( then part ). On the contrary, the grammar in figure 6 defines: When you find a determiner ( if part ), this determiner is either in genitive, either in accusative, or it is in nominative and the following nominal group is also in nominative. Finally, we have enriched the nominative graph, in the sense that the description in the then part is more detailed as grammars were applied to a larger corpus and we came across more different grammatical categories that followed a determiner in nominative. The letter <E> in a box means that its content is optional. In the following text automaton (figure 7), one can see the results of the Elag grammar for the nominative case. In particular, when the form η is a determiner, then the adjective that follows is in nominative. When it is an abbreviation or a conjunction, the grammar is not applied and no ambiguity is eliminated. 12 Some indicative lexicon-grammars are presented by Kyriacopoulou (2005).

10 Figure 6: Elag grammar for nominative

11 Figure 7. Text automaton after applying the Elag grammar for nominative. (e.g The Community financial support can reach 50% of the total expenses for the project and cannot exceed ECU) The genitive case For most nouns, the genitive case is not ambiguous with the nominative, accusative or vocative cases. The indeclinable nouns and the masculine nouns ending in ας are the only exception to this (e.g.12). The Elag grammar for genitive is, thus, created for these exceptions. The ambiguities are eliminated, for once more, describing some constraints in terms of context. The context requiring genitive is limited to some prepositions (λόγω: because of, µεταξύ: among/between, µέσω: by/through) (e.g. 13).

12 12. ασανσέρ N:Nns:Gns:Ans:Vns:Nnp:Gnp:Anp:Vnp (elevator) 13. Ανέβηκαν µε τις σκάλες λόγω χαλασµένου ΑΣΑΝΣΕΡ (They went up by the stairs because of a broken ELEVATOR) ασανσέρ N:Gns Similarly to the nominative graph, in order to increase the applicability of the genitive grammar (figure 8), we removed most of the if part apart from all the prepositions requiring a genitive. The best applicability percentage is achieved, because there is less information in the if part and the grammar is applied to more sentences. Moreover, we added another nominal group in genitive because it is often noticed in texts. The nominal groups are presented in a linear succession so as to be more legible. Figure 8: Elag grammar for genitive The results obtained after the application of the genitive grammar are shown in the following text automaton (figure 9). In particular, after the application of the genitive graph, the word Ίντερνετ (Internet) is recognised as a genitive form of the singular and plural when following the preposition. Nevertheless, the word Ίντερνετ cannot be a plural; it is an error due to a false registration in the dictionary.

13 Figure 9. Text automaton after applying the Elag grammar for genitive. (e.g The payments will be settled by the Internet) The accusative case Ambiguities between accusative and other cases may be found in all declensions. Here is a representative example representative for every genre: 14. γίγαντα N:Ams:Vms (giant) 15. χώρα N:Nfs:Afs:Vfs (country) 16. παπούτσι N:Nns:Ans:Vns (shoe) In order to define the accusative case, we described the sequences following certain prepositions. If the accusative grammar created initially is compared to the one below (figure 10) the following differences will be found:

14 - Some prepositions have been removed from the if part as they have been seen in texts before a nominative; - The prepositional determiner has been added (e.g. στο :to the) in the if part ; - The symbol % has been added after a number, because there may be a percentage; - Another adjective preceding a conjunction or punctuation has been added (e.g. Έφυγε µε ένα ΩΡΑΙΟ ΚΑΙ γρήγορο αυτοκίνητο: He left on a BEAUTIFUL AND quick car); - A personal pronoun that could precede the noun has been added (e.g. Έφυγε µε το ωραίο ΤΟΥ αµάξι: He left on HIS beautiful car); - The prepositions in the if part have been also found before an abbreviation or punctuation sign (e.g. Απαγορεύεται να έρθετε µε: : You are not allowed to have with you: ). After applying the above graph, we obtained the results shown in figure 11. In particular, the word τοµέα is recognized as an accusative, because it is following the prepositional determiner στον. 3. Conclusions Perspectives All grammars presented above, combined together, have been verified in electronic corpora. The ambiguities eliminated constitute only a small part of the ones existing in Modern Greek. Thus, more grammars should be created, which, along with the grammars presented above, will be applied to corpora as a united rule. Our aim is to have a Greek corpus semi-automatically labelled (every word will have only one morphological description) and this can only be attained with disambiguation grammars constantly tested in large corpora and updated electronic dictionaries. A semi-automatically labelled corpus could serve all computational linguistics applications (e.g. machine translation, automatic summarisation), which do not exist at a satisfactory level.

15 Figure 10: Elag grammar for accusative

16 Figure 11. Text automaton after applying the accusative Elag grammar. (e.g. Project of community action on cultural inheritance) REFERENCES Anastassiadis-Symeonidis, A., Kyriakopoulou, T., Sklavounou, E., Thilikos, I. & Voskaki, R. 2000: A system for analysing texts in Modern Greek: representing and solving ambiguities. Proceedings of COMLEX 2000, Workshop on Computational Lexicography and Multimedia Dictionaries. Patras: University of Patras, Blanc, O. 2003: Manual ELAG. Blanc, O. & Dister, A. 2004: Automates lexicaux avec structure de traits. Actes RECITAL Fès, Blanc, O., Ioannidou, K. & Voskaki, R. 2005: Automatic elimination of lexical ambiguities in Modern Greek: presentation of the Elag system. Μελέτες για την Ελληνική Γλώσσα 25, Βοσκάκη, Ρ. & Θηλυκός, Ι. 2003: «Αναπαράσταση των ουσιαστικοποιηµένων επιθέτων της Νέας Ελληνικής µε διαδικασίες

17 αυτοµατισµού πεπερασµένων καταστάσεων» Μελέτες για την Ελληνική Γλώσσα 23, Βοσκάκη, Ρ. & Καζαντζή,. 2004: «Εξάλειψη αµφισηµιών σε ουσιαστικοποιηµένα επίθετα και επιρρήµατα». Πρακτικά 6 ου ιεθνούς Συνέδριου Ελληνικής Γλωσσολογίας Εργαστηρίου Γλωσσολογίας του Πανεπιστηµίου Κρήτης. Ρέθυµνο. ISBN: Βοσκάκη, Ρ. & Μπακούρα, Σ. 2004: «Εξάλειψη αµφισηµιών των νοµισµατικών µονάδων, συµβόλων και γλωσσών στη Νέα Ελληνική και ενσωµάτωσή τους σε συστήµατα αυτόµατης ανάλυσης κειµένων». Μελέτες για την Ελληνική Γλώσσα 24, Holton, D., Mackridge, P. & Phillipaki-Warburton, I. 2002: Γραµµατική της ελληνικής γλώσσας. Αθήνα: Πατάκης. Θηλυκός, Ι. 2000: Ένα σύστηµα ανάλυσης κειµένων της Νέας Ελληνικής: Αναπαράσταση και εξάλειψη αµφισηµιών. ιπλωµατική εργασία. Θεσσαλονίκη: Αριστοτέλειο Πανεπιστήµιο Θεσσαλονίκης. Κλαίρης, Χ. & Μπαµπινιώτης, Γ. 2001: Γραµµατική της Νέας Ελληνικής Ι. Το όνοµα. Αθήνα: Ελληνικά Γράµµατα. Kyriacopoulou, T. 2005: L Analyse Automatique des Textes Écrits: Les Cas du Grec Moderne. Thessalonique: University Studio Press. Laporte, E. 1994: Experiments in Lexical Disambiguation using local grammars. In F. Kiefer, G. Kiss & J. Pajzs (eds.), Papers in Computational Lexicography (COMLEX). Budapest, Laporte, E. 2001: Reduction of lexical ambiguity. Lingvisticae Investigationes XXIV:1. Amsterdam/ Philadelphia: John Benjamins, Laporte, E. & Monceaux, A. 1999: Elimination of lexical ambiguities by grammars. The ELAG system. Lingvisticae Investigationes VII:2. Amsterdam/ Philadelphia: John Benjamins, Paumier, S. 2002: Manual UNITEX. Silberztein, M. 1999: Finite State Transducers and the Processing of Natural Languages. Tutorial Notes, INTEX [electronic edition]. Σκλαβούνου, Ε. 1995: «Ένα παράδειγµα λεξιλογικής αναπαράστασης και επεξεργασίας µε πεπερασµένα αυτόµατα». Μελέτες για την Ελληνική Γλώσσα 15,