Papers with neural named entity recognition models

2 papers
The Utility and Interplay of Gazetteers and Entity Segmentation for Named Entity Recognition in English (2021.findings-acl)

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Challenge: Recent papers introduce methods to incorporate gazetteer features and entity segmentation techniques in neural named entity recognition models.
Approach: They propose to integrate gazetteer features and entity segmentation techniques into neural named entity recognition models.
Outcome: The proposed methods improve entity segmentation and not just entity typing.
Soft Gazetteers for Low-Resource Named Entity Recognition (2020.acl-main)

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Challenge: Existing named entity recognition models use gazetteers to improve performance, but they are limited in coverage and do not exist in low-resource languages.
Approach: They propose a method that integrates Wikipedia information into named entity models by cross-lingual entity linking.
Outcome: The proposed method improves on four low-resource languages with Wikipedia . it incorporates available information from english knowledge bases into neural models .

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