How Do Your Biomedical Named Entity Recognition Models Generalize to Novel Entities?

Author:

Kim Hyunjae1ORCID,Kang Jaewoo1ORCID

Affiliation:

1. Department of Computer Science and Engineering, Korea University, Seoul, South Korea

Funder

National Research Foundation of Korea

Korea Health Technology Research and Development Project through the Korea Health Industry Development Institute

Ministry of Health & Welfare, Republic of Korea

Ministry of Science and ICT (MSIT) under the ICT Creative Consilience Program

Institute for Information & Communications Technology Planning & Evaluation (IITP), South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Reference52 articles.

1. Entity-switched datasets: An approach to auditing the in-domain robustness of named entity recognition models;agarwal;arXiv 2004 04123,2020

2. Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization

3. TaggerOne: joint named entity recognition and normalization with semi-Markov Models

4. A neural network multi-task learning approach to biomedical named entity recognition

5. Conditional random fields: Probabilistic models for segmenting and labeling sequence data;lafferty;Proc 18th Int Conf Mach Learn (ICML),2001

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