Fine-grained Entity Recognition of Business Contract Based on Lexicon Enhancement
The information extraction of the parties,the basic contract information,the contract terms and other fine-grained entities in the contract text can effectively improve the efficiency of contract review and empower auto-mated contract management.To address the challenge of complexity and subtlety of entities in the contract,this pa-per proposes a new fine-grained entity recognition model named BLBC-CFER based on lexicon enhancement.It em-ploys the character-level enhancements provided by pre-trained language models,word-level enhancements provided by character-plus-word embeddings and word-level enhancements provided by lexical set structure embeddings.Based on these,it obtains the optimal sequence of tokens through deep neural networks.Experiments on a self-con-structed fine-grained entity corpus of business contracts and two public data sets demonstrate the superior perform-ance of the proposed method.
万方数据
维普
