taishan1994/pytorch_triple_extraction
基于pytorch的中文三元组提取（命名实体识别+关系抽取）
This project helps operations engineers or data scientists extract structured information from unstructured Chinese text, particularly for technical reports like automobile fault descriptions. It takes raw Chinese text and a list of predefined relationships (e.g., '部件故障' - component failure, '性能故障' - performance issue) as input. The output is a list of subject-object-relation triplets, such as ('发动机', '熄火', '部件故障'), making it easier to build knowledge graphs or analyze textual data.
362 stars. No commits in the last 6 months.
Use this if you need to automatically identify entities (like 'engine' or 'failure') and the relationships between them (like 'engine' has a 'component failure' of 'stalling') from large volumes of Chinese text.
Not ideal if your data is not in Chinese or if you primarily need to extract entities without considering their relationships, or if you need a pre-trained model for a highly specialized domain without further training.
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Python
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Last pushed
May 12, 2023
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