Joint Dependency Parsing and Multiword Expression Tokenisation

Abstract : Complex conjunctions and determiners are often considered as pretokenized units in parsing. This is not always realistic, since they can be ambiguous. We propose a model for joint dependency parsing and multiword expressions identification, in which complex function words are represented as individual tokens linked with morphological dependencies. Our graph-based parser includes standard second-order features and verbal subcategoriza-tion features derived from a syntactic lexicon .We train it on a modified version of the French Treebank enriched with morphological dependencies. It recognizes 81.79% of ADV+que conjunctions with 91.57% precision, and 82.74% of de+DET determiners with 86.70% precision.
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Alexis Nasr, Carlos Ramisch, José Deulofeu, André Valli. Joint Dependency Parsing and Multiword Expression Tokenisation. Annual Meeting of the Association for Computational Linguistics, Jul 2015, Beijing, China. pp.1116 - 1126. ⟨hal-01464872⟩



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