Improving Dependency Parsers with Supertags

Hiroki Ouchi, Kevin Duh, Yuji Matsumoto
2014 Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers  
Transition-based dependency parsing systems can utilize rich feature representations. However, in practice, features are generally limited to combinations of lexical tokens and part-of-speech tags. In this paper, we investigate richer features based on supertags, which represent lexical templates extracted from dependency structure annotated corpus. First, we develop two types of supertags that encode information about head position and dependency relations in different levels of granularity.
more » ... en, we propose a transition-based dependency parser that incorporates the predictions from a CRF-based supertagger as new features. On standard English Penn Treebank corpus, we show that our supertag features achieve parsing improvements of 1.3% in unlabeled attachment, 2.07% root attachment, and 3.94% in complete tree accuracy.
doi:10.3115/v1/e14-4030 dblp:conf/eacl/OuchiDM14 fatcat:fldbauaeibfyzdekc3srzpknwy