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2017 EACL EACL 2017

Improving a Strong Neural Parser with Conjunction-Specific Features

AbstractWhile 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.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

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