arXiv:2006.01372 공식 코드 · Papers with Code

Embeddings of Label Components for Sequence Labeling: A Case Study of Fine-grained Named Entity Recognition

Takuma Kato, Kaori Abe, Hiroki Ouchi, Shumpei Miyawaki, Jun Suzuki, Kentaro Inui

제출 2020-06-02

원문 초록

In general, the labels used in sequence labeling consist of different types of elements. For example, IOB-format entity labels, such as B-Person and I-Person, can be decomposed into span (B and I) and type information (Person). However, while most sequence labeling models do not consider such label components, the shared components across labels, such as Person, can be beneficial for label prediction. In this work, we propose to integrate label component information as embeddings into models. Through experiments on English and Japanese fine-grained named entity recognition, we demonstrate that the proposed method improves performance, especially for instances with low-frequency labels.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2504.16007공통 태그 Named Entity Recognition (NER), named-entity-recognition, Named Entity Recognition공식 코드 · Papers with Code

Methods for Recognizing Nested Terms

토론

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