Labeling gaps between words: Recognizing overlapping mentions with mention separators

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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.

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APA

Muis, A. O., & Lu, W. (2017). Labeling gaps between words: Recognizing overlapping mentions with mention separators. In EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 2608–2618). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d17-1276

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