Alibaba-NLP/CLNER
[ACL-IJCNLP 2021] Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
This project helps natural language processing (NLP) developers enhance the accuracy of Named Entity Recognition (NER) models. It takes raw text data as input and produces more accurate NER tags for entities like names, organizations, or locations. Developers and researchers working on advanced text analysis would use this to improve the quality of their entity extraction tasks.
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Use this if you are an NLP developer or researcher looking to significantly improve the performance of your Named Entity Recognition models by leveraging external contextual information and cooperative learning techniques.
Not ideal if you need a simple, out-of-the-box NER solution for basic entity extraction without delving into advanced model training and configuration.
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Python
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Last pushed
Nov 20, 2022
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