Improving a strong neural parser with conjunction-specific features

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Abstract

While dependency parsers reach very high overall accuracy, some dependency relations are much harder than others. In particular, dependency parsers perform poorly in coordination construction (i.e., correctly attaching the conj relation). We extend a state-of-the-art dependency parser with conjunction-specific features, focusing on the similarity between the conjuncts head words. Training the extended parser yields an improvement in conj attachment as well as in overall dependency parsing accuracy on the Stanford dependency conversion of the Penn TreeBank.

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APA

Ficler, J., & Goldberg, Y. (2017). Improving a strong neural parser with conjunction-specific features. In 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference (Vol. 2, pp. 343–348). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/e17-2055

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