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Example-Based Named Entity Recognition

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arxiv 2008.10570 v1 pith:V7JKE5HD submitted 2020-08-24 cs.CL cs.IR

Morteza Ziyadi , Yuting Sun , Abhishek Goswami , Jade Huang , Weizhu Chen This is my paper · ORCID
classification cs.CLcs.IR
keywords entityapproachexample-basednamedrecognitionbettercallcomparison
verification ladder T0 review T1 audit T2 compute T3 formal
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We present a novel approach to named entity recognition (NER) in the presence of scarce data that we call example-based NER. Our train-free few-shot learning approach takes inspiration from question-answering to identify entity spans in a new and unseen domain. In comparison with the current state-of-the-art, the proposed method performs significantly better, especially when using a low number of support examples.

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Cited by 1 Pith paper

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  1. FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework

    cs.CL 2025-02 conditional novelty 5.0 of 10

    FewTopNER reports that adding a topic-modeling branch to a prototype-based few-shot NER model improves multilingual F1 by 2.5 to 4.0 points and increases topic coherence scores.

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