Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separators

Aldrian Obaja Muis, Wei Lu


Abstract
In this paper, we propose a new model that is capable of recognizing overlapping mentions. We introduce a novel notion of mention separators that can be effectively used to capture how mentions overlap with one another. On top of a novel multigraph representation that we introduce, we show that efficient and exact inference can still be performed. We present some theoretical analysis on the differences between our model and a recently proposed model for recognizing overlapping mentions, and discuss the possible implications of the differences. Through extensive empirical analysis on standard datasets, we demonstrate the effectiveness of our approach.
Anthology ID:
D17-1276
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2608–2618
Language:
URL:
https://www.aclweb.org/anthology/D17-1276
DOI:
10.18653/v1/D17-1276
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http://aclanthology.lst.uni-saarland.de/D17-1276.pdf
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