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In the field of Natural Language Processing (NLP), Named Entity Recognition (NER) is recognized as a critical technology, employed across a wide array of applications. Traditional methodologies for annotating datasets for NER models are challenged by
Externí odkaz:
http://arxiv.org/abs/2404.01334
Autor:
Ishibashi T; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Aoyama R; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Hotta H; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Watanabe I; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Takahashi Y; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Matsumoto S; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Yamaki R; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN., Anazawa U; Orthopaedics, Tokyo Dental College Ichikawa General Hospital, Ichikawa, JPN.
Publikováno v:
Cureus [Cureus] 2022 Sep 05; Vol. 14 (9), pp. e28809. Date of Electronic Publication: 2022 Sep 05 (Print Publication: 2022).
