# Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separators

arXiv: https://arxiv.org/abs/1810.09073 · HTML: https://mlsanity.com/paper/1810.09073/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Oct 2018.

## Built on by (most cited first, 14 of 14)

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- [A dynamic programming algorithm for span-based nested named-entity recognition in O(n^2)](https://mlsanity.com/paper/2210.04738/) (2022)
- [BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge](https://mlsanity.com/paper/2107.09429/) (2021)
- [NameTag 3: A Tool and a Service for Multilingual/Multitagset NER](https://mlsanity.com/paper/2506.05949/) (2025)
- [Effect of depth order on iterative nested named entity recognition models](https://mlsanity.com/paper/2104.01037/) (2021)
- [Semantic Norm Recognition and its application to Portuguese Law](https://mlsanity.com/paper/2203.05425/) (2022)
- [Nested Named Entity Recognition as Holistic Structure Parsing](https://mlsanity.com/paper/2204.08006/) (2022)
- [S2F-NER: Exploring Sequence-to-Forest Generation for Complex Entity Recognition](https://mlsanity.com/paper/2310.18944/) (2023)
- [Nested Named Entity Recognition in Plasma Physics Research Articles](https://mlsanity.com/paper/2602.11163/) (2026)

## Abstract (arXiv)

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.