Improving Arabic Dependency Parsing with Form-based and Functional Morphological Features

Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pages 1586–1596, Portland, Oregon, June 19-24, 2011. c⃝2011 Association for Computational Linguistics Improving Arabic Dependency Parsing with Form-based and Functional Morphological Features Yuval Marton T.J. Watson Research Center IBM yymarton@us.ibm.com Nizar Habash and Owen Rambow Center for Computational Learning Systems Columbia University {habash,rambow}@ccls.columbia.edu Abstract We explore the contribution of morphologi- cal features – both lexical and inflectional – to dependency parsing of Arabic, a morpho- logically rich language. Using controlled ex- periments, we find that definiteness, person, number, gender, and the undiacritzed lemma are most helpful for parsing on automatically tagged input. We further contrast the contri- bution of form-based and functional features, and show that functional gender and number (e.g., “broken plurals”) and the related ratio- nality feature improve over form-based fea- tures. It is the first time functional morpho- logical features are used for Arabic NLP. 1 Introduction Parsers need to learn the syntax of the modeled lan- guage in order to project structure on newly seen sentences. Parsing model design aims to come up with features that best help parsers to learn the syn- tax and choose among different parses. One as- pect of syntax, which is often not explicitly mod- eled in parsing, involves morphological constraints on syntactic structure, such as agreement, which of- ten plays an important role in morphologically rich languages. In this paper, we explore the role of morphological features in parsing Modern Standard Arabic (MSA). For MSA, the space of possible mor- phological features is fairly large. We determine which morphological features help and why. We also explore going beyond the easily detectable, reg- ular form-based (“surface”) features, by represent- ing functional values for some morphological fea- tures. We expect that representing lexical abstrac- tions and inflectional features participating in agree- ment relations would help parsing quality, but other inflectional features would not help. We further ex- pect functional features to be superior to surface- only features. The paper is structured as follows. We first present the corpus we use (Section 2), then rele- vant Arabic linguistic facts (Section 3); we survey related work (Section 4), describe our experiments (Section 5), and conclude with an analysis of pars- ing error types (Section 6). 2 Corpus We use the Columbia Arabic Treebank (CATiB) (Habash and Roth, 2009). Specifically, we use the portion converted automatically from part 3 of the Penn Arabic Treebank (PATB) (Maamouri et al., 2004) to the CATiB format, which enriches the CATiB dependency trees with full PATB morpho- logical information. CATiB’s dependency represen- tation is based on traditional Arabic grammar and emphasizes syntactic case relations. It has a re- duced POS tagset (with six tags only – henceforth CATIB6), but a standard set of eight dependency re- lations: SBJ and OBJ for subject and (direct or indi- rect) object, respectively, (whether they appear pre- or post-verbally); IDF for the idafa (possessive) re- lation; MOD for most other modifications; and other less common relations that we will not discuss …

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