Using CCG categories to improve Hindi dependency parsing
Bharat Ram Ambati, Tejaswini Deoskar and Mark Steedman
The 51st Annual Meeting of the Association for Computational Linguistics - Short Papers (ACL Short Papers 2013)
Sofia, Bulgaria, August 4-9, 2013
We show that informative lexical categories from a strongly lexicalised formalism such as Combinatory Categorial Grammar (CCG) can improve dependency parsing of Hindi, a free word order language.We first describe a novel way to obtain a CCG lexicon and treebank from an existing dependency treebank using a CCG parser. We use the output of a supertagger trained on the CCGbank as a feature for a state-of-the art Hindi dependency parser (Malt). Our results show that using CCG categories improves the accuracy of Malt on long distance dependencies, for which it is known to have weak rates of recovery.
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