# Improving a Strong Neural Parser with Conjunction-Specific Features

arXiv: https://arxiv.org/abs/1702.06733 · HTML: https://mlsanity.com/paper/1702.06733/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Feb 2017.

## Built on by (most cited first, 2 of 2)

- [CoRec: An Easy Approach for Coordination Recognition](https://mlsanity.com/paper/2311.18712/) (2023)
- [Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction](https://mlsanity.com/paper/2107.06905/) (2021)

## Abstract (arXiv)

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.