Abstract
This paper is concerned with statistical methods for treating long-distance dependencies. We focus in particular on a case of substantial recent interest: that of long-distance dependency effects in entity extraction. We introduce a new approach to capturing these effects through a simple feature copying preprocess, and demonstrate substantial performance gains on several entity extraction tasks. © 2009 Association for Computational Linguistics.
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CITATION STYLE
Vilain, M., Huggins, J., & Wellner, B. (2009). A simple feature-copying approach for long-distance dependencies. In CoNLL 2009 - Proceedings of the Thirteenth Conference on Computational Natural Language Learning (pp. 192–200). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1596374.1596405
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