Kai-Wei Chang, Rajhans Samdani, Dan Roth

EMNLP 2013

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Abstract

Coreference resolution is a well known clustering task in Natural Language Processing. In this paper, we describe the Latent Left Linking model (L3M), a novel, principled, and linguistically motivated latent structured prediction approach to coreference resolution.

We show that L3M admits efficient inference and can be augmented with knowledge-based constraints; we also present a fast stochastic gradient based learning.

Experiments on ACE and Ontonotes data show that L3M and its constrained version, CL3M, are more accurate than several state-of-the-art approaches as well as some structured prediction models proposed in the literature.

Bib entry

@inproceedings{ChangSaRo13,
author = {Kai-Wei Chang and Rajhans Samdani and Dan Roth},
title= {{A Constrained Latent Variable Model for Coreference Resolution}},
booktitle = {EMNLP},
year = {2013}
}