Dependency-based Analysis for Tagalog Sentences

Dependency-based Analysis for Tagalog Sentences ⋆ Erlyn Manguilimotan and Yuji Matsumoto Graduate School of Information Science Nara Institute of Science and Technology 8916-5, Takayama, Ikoma, Nara, Japan, 630-0192 {erlyn-m, matsu}@is.naist.jp Abstract. Interest in dependency parsing increased because of its efficiency to represent languages with flexible word order. Many research have applied dependency-based syntactic analysis to different languages and results vary depending on the nature of the language. Lan- guages with more flexible word order structure tend to have lower performances compared to more fixed word order languages. This work presents, for the first time, a dependency- based parsing for Tagalog language, a free word order language. The parser is tested using manually assigned POS and auto-assigned POS data. Experiment results show an average of about 78% accuracy on unlabeled attachment scores, and about 24% on complete depen- dency scores. As the position of the sentence head is not fixed, we look into sentence head accuracy as assigned by the parser. Results show that around 83% - 84% of the sentence head are assigned correctly. Keywords: Dependency parsing, Tagalog, free word order, morphological information 1 Introduction Morphologically rich languages (MRL) are languages where word-level information affects syn- tactic relations (Tsarfaty et al., 2010). Recently, MRL have drawn attention in statistical parsing. While state-of-the-art parsers brought high performance scores for languages such as English and Japanese, this is not true for MRLs. Dependency parsing techniques and approaches are devel- oped for languages with relatively fix word orders; however, they are not successful when applied for MRL. In the 2007 CoNLL Shared Task on Dependency parsing, languages such English and Catalan have top scores while languages with free word order and higher degree of inflection have lower scores (e.g. Arabic, Basque)(Nivre et al., 2007). Although factors such as small data can contribute to the degradation of the parser performance, linguistic factors such as morphologi- cal inflection and freeness in word order have made it difficult to parse MRL with models and techniques developed with languages like English (Tsarfaty et al., 2010). In this paper we look into a state-of-art dependency parser applied on Tagalog language. Prior to this work, there is no known data-driven dependency-based parsing for Tagalog. Tagalog is the national language of the Philippines and is a member of the Austronesian language family. It is a morphologically rich language which has affixations, stress shifting, consonant alteration, and reduplication (Nelson, 2004). Affixations include prefixation, infixation, suffixation and circum- fixation, where two or three affixes are attached to a root word. Highly inflected verbs show verbal focus (actor, object, etc.) and aspect (perfective, imperfective, and contemplated). Aside from its morphological complexity, sentences are word order free. In Tagalog sentences, predicate comes first for pragmatically unmarked clauses but the NP complements take flexible positions in the sentence (Kroeger, 1993). Figure 1 showing possible orders of the complements ⋆ The authors would like to thank the Center for Language Technologies of De La Salle University, Manila, Philippines for allowing us to use the Tagalog POS …

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