Statistical Dependency Parsing for Turkish

Statistical Dependency Parsing of Turkish G¨uls¸en Eryiˇgit Department of Computer Engineering Istanbul Technical University Istanbul, 34469, Turkey gulsen@cs.itu.edu.tr Kemal Oflazer Faculty of Engineering and Natural Sciences Sabanci University Istanbul, 34956, Turkey oflazer@sabanciuniv.edu Abstract This paper presents results from the first statistical dependency parser for Turkish. Turkish is a free-constituent order lan- guage with complex agglutinative inflec- tional and derivational morphology and presents interesting challenges for statisti- cal parsing, as in general, dependency re- lations are between “portions” of words – called inflectional groups. We have explored statistical models that use dif- ferent representational units for parsing. We have used the Turkish Dependency Treebank to train and test our parser but have limited this initial exploration to that subset of the treebank sentences with only left-to-right non-crossing depen- dency links. Our results indicate that the best accuracy in terms of the dependency relations between inflectional groups is obtained when we use inflectional groups as units in parsing, and when contexts around the dependent are employed. 1 Introduction The availability of treebanks of various sorts have fostered the development of statistical parsers trained with the structural data in these tree- banks. With the emergence of the important role of word-to-word relations in parsing (Charniak, 2000; Collins, 1996), dependency grammars have gained a certain popularity; e.g., Yamada and Mat- sumoto (2003) for English, Kudo and Matsumoto (2000; 2002), Sekine et al. (2000) for Japanese, Chung and Rim (2004) for Korean, Nivre et al. (2004) for Swedish, Nivre and Nilsson (2005) for Czech, among others. Dependency grammars represent the structure of the sentences by positing binary dependency relations between words. For instance, Figure 1 Figure 1: Dependency Relations for a Turkish and an English sentence shows the dependency graph of a Turkish and an English sentence where dependency labels are shown annotating the arcs which extend from de- pendents to heads. Parsers employing CFG-backbones have been found to be less effective for free-constituent- order languages where constituents can easily change their position in the sentence without modifying the general meaning of the sentence. Collins et al. (1999) applied the parser of Collins (1997) developed for English, to Czech, and found that the performance was substantially lower when compared to the results for English. 2 Turkish Turkish is an agglutinative language where a se- quence of inflectional and derivational morphemes get affixed to a root (Oflazer, 1994). At the syntax level, the unmarked constituent order is SOV, but constituent order may vary freely as demanded by the discourse context. Essentially all constituent orders are possible, especially at the main sen- tence level, with very minimal formal constraints. In written text however, the unmarked order is dominant at both the main sentence and embedded clause level. Turkish morphotactics is quite complicated: a given word form may involve multiple derivations and the number of word forms one can generate from a nominal or verbal root is theoretically in- finite. Derivations in Turkish are very produc- tive, and the syntactic relations that a word is in- 89 volved …

Content truncated to 500 words