Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separators
About
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.
Aldrian Obaja Muis, Wei Lu• 2018
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Nested Named Entity Recognition | ACE 2004 (test) | F1 Score64.5 | 166 | |
| Nested Named Entity Recognition | ACE 2005 (test) | F1 Score63.1 | 153 | |
| Nested Named Entity Recognition | GENIA (test) | F1 Score70.8 | 140 | |
| Named Entity Recognition | CoNLL English 2003 (test) | F1 Score84.3 | 135 | |
| Entity extraction | ACE05 (test) | F1 Score63.1 | 53 | |
| Named Entity Recognition | ACE05 | F1 Score63.1 | 38 | |
| Named Entity Recognition | GENIA | F1 Score70.8 | 37 | |
| Nested Mention Detection | ACE2005 (test) | F1 Score63.1 | 30 | |
| Overlapping Mention Recognition | GENIA (standard) | Precision75.4 | 18 | |
| Overlapping Mention Recognition | ACE 2005 (standard) | Precision69.1 | 17 |
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