2019 NAACL NAACL 2019

Decomposed Local Models for Coordinate Structure Parsing

Abstract

AbstractWe propose a simple and accurate model for coordination boundary identification. Our model decomposes the task into three sub-tasks during training; finding a coordinator, identifying inside boundaries of a pair of conjuncts, and selecting outside boundaries of it. For inference, we make use of probabilities of coordinators and conjuncts in the CKY parsing to find the optimal combination of coordinate structures. Experimental results demonstrate that our model achieves state-of-the-art results, ensuring that the global structure of coordinations is consistent.

🧭 Keyword Pioneer — cky parsing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing