Automatic noisy label correction for fine-grained entity typing

• Main Authors: PAN, Weiran, WEI, Wei, ZHU, Feida
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Natural language processing; Named entities; Natural language processing: applications; Natural language processing: information retrieval and text mining; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7753; https://ink.library.smu.edu.sg/context/sis_research/article/8756/viewcontent/automatic_noisy.pdf
• Institution: Singapore Management University

Fine-grained entity typing (FET) aims to assign proper semantic types to entity mentions according to their context, which is a fundamental task in various entity-leveraging applications. Current FET systems usually establish on large-scale weaklysupervised/distantly annotation data, which may conta...