BERT-NER-Pytorch and NER-BERT-pytorch
About BERT-NER-Pytorch
lonePatient/BERT-NER-Pytorch
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
This project helps natural language processing engineers and researchers extract specific pieces of information, such as names, locations, or organizations, from Chinese text. It takes raw Chinese sentences and outputs the same text with each character labeled by the type of entity it belongs to. This is ideal for NLP practitioners working on information extraction or text analysis tasks for the Chinese language.
About NER-BERT-pytorch
lemonhu/NER-BERT-pytorch
PyTorch solution of named entity recognition task Using Google AI's pre-trained BERT model.
This project helps you automatically identify and categorize key entities like people, organizations, and locations within Chinese text. You input raw Chinese text data, and it outputs the same text with specific words or phrases tagged as a 'person,' 'organization,' or 'location.' This is ideal for natural language processing engineers or data scientists who need to extract structured information from unstructured Chinese documents.
Scores updated daily from GitHub, PyPI, and npm data. How scores work