1. Dependency Parsing of Turkish
- Author
-
NivreJoakim, OflazerKemal, and EryiğitGülşen
- Subjects
FOS: Computer and information sciences ,Linguistics and Language ,Turkish ,Computer science ,Memoization ,P Philology. Linguistics ,Top-down parsing ,computer.software_genre ,Language and Linguistics ,200402 Computational Linguistics ,Parser combinator ,Artificial Intelligence ,Dependency grammar ,QA Mathematics ,QA075 Electronic computers. Computer science ,Parsing ,business.industry ,language.human_language ,Computer Science Applications ,TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES ,Applied Computer Science ,QA076 Computer software ,language ,FOS: Languages and literature ,Top-down parsing language ,S-attributed grammar ,Artificial intelligence ,Deterministic parsing ,business ,80107 Natural Language Processing ,computer ,Syntactic parsing ,Natural language processing ,Bottom-up parsing - Abstract
The suitability of different parsing methods for different languages is an important topic in syntactic parsing. Especially lesser-studied languages, typologically different from the languages for which methods have originally been developed, pose interesting challenges in this respect. This article presents an investigation of data-driven dependency parsing of Turkish, an agglutinative, free constituent order language that can be seen as the representative of a wider class of languages of similar type. Our investigations show that morphological structure plays an essential role in finding syntactic relations in such a language. In particular, we show that employing sublexical units called inflectional groups, rather than word forms, as the basic parsing units improves parsing accuracy. We test our claim on two different parsing methods, one based on a probabilistic model with beam search and the other based on discriminative classifiers and a deterministic parsing strategy, and show that the usefulness of sublexical units holds regardless of the parsing method. We examine the impact of morphological and lexical information in detail and show that, properly used, this kind of information can improve parsing accuracy substantially. Applying the techniques presented in this article, we achieve the highest reported accuracy for parsing the Turkish Treebank.
- Published
- 2008