English

Improving a Strong Neural Parser with Conjunction-Specific Features

Computation and Language 2017-02-23 v1

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.

Keywords

Cite

@article{arxiv.1702.06733,
  title  = {Improving a Strong Neural Parser with Conjunction-Specific Features},
  author = {Jessica Ficler and Yoav Goldberg},
  journal= {arXiv preprint arXiv:1702.06733},
  year   = {2017}
}
R2 v1 2026-06-22T18:25:05.572Z