June 11, 2024, 4:43 a.m. | Tanay Komarlu, Minhao Jiang, Xuan Wang, Jiawei Han

cs.CL updates on arXiv.org arxiv.org

arXiv:2305.12307v2 Announce Type: replace
Abstract: Fine-grained entity typing (FET), which assigns entities in text with context-sensitive, fine-grained semantic types, is a basic but important task for knowledge extraction from unstructured text. FET has been studied extensively in natural language processing and typically relies on human-annotated corpora for training, which is costly and difficult to scale. Recent studies explore the utilization of pre-trained language models (PLMs) as a knowledge base to generate rich and context-aware weak supervision for FET. However, a …

abstract arxiv basic context cs.cl extraction fine-grained human important knowledge language language model language processing natural natural language natural language processing ontology processing replace semantic text training type types typing unstructured

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