mlsanityData to 14 Oct 2026

GlobalNER: Incorporating Non-local Information into Named Entity Recognition

arXiv 2303.02915 ↗First posted 6 Mar 2023cs.CL cs.AIcited by 0

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Abstract (arXiv)

Nowadays, many Natural Language Processing (NLP) tasks see the demand for incorporating knowledge external to the local information to further improve the performance. However, there is little related work on Named Entity Recognition (NER), which is one of the foundations of NLP. Specifically, no studies were conducted on the query generation and re-ranking for retrieving the related information for the purpose of improving NER. This work demonstrates the effectiveness of a DNN-based query generation method and a mention-aware re-ranking architecture based on BERTScore particularly for NER. In the end, a state-of-the-art performance of 61.56 micro-f1 score on WNUT17 dataset is achieved.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 49 references that are in the map. First posted on arXiv 6 Mar 2023.

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17 of 49 references.

References · 17

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5 more
  1. 2021Improving Named Entity Recognition by External Context Retrieving and Cooperative Learningcited by 76
  2. 2022T-NER: An All-Round Python Library for Transformer-based Named Entity Recognitioncited by 37
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  5. 2019Giveme5W1H: A Universal System for Extracting Main Events from News Articlescited by 15

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