Affiliation:
1. School of Computer Science and Engineering, North Minzu University, 750021, China
Abstract
To solve the problem of unclear entity boundaries and low recognition accuracy in Chinese text, we construct the crop dataset and propose a Bert-binary-based entity link method. Candidate entity sets are generated through entity matching in multiple data sources. The Bert-binary model is called to calculate the correct probability of the candidate entity, and the entity with the highest score is screened for linking. In comparative experiments with three models on the crop dataset, the
value is increased by 2.5% on the best method or by 8.8% on average. The experimental results show the effectiveness of Bert-binary method in this paper.
Funder
Key Laboratory of Images & Graphics Intelligent Processing of State Ethnic Affairs Commission
Subject
Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering
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