Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 186 tok/s
Gemini 2.5 Pro 55 tok/s Pro
GPT-5 Medium 36 tok/s Pro
GPT-5 High 41 tok/s Pro
GPT-4o 124 tok/s Pro
Kimi K2 184 tok/s Pro
GPT OSS 120B 440 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Improving a Strong Neural Parser with Conjunction-Specific Features (1702.06733v1)

Published 22 Feb 2017 in cs.CL

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.

Citations (7)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.