ranxi2001/information-extraction-policy-news
政策新闻领域 实体识别+关系抽取 基于4000句txt微调得到
This project helps policy analysts, researchers, or news aggregators quickly understand large volumes of text related to policy and news. It takes unstructured text documents as input and extracts key entities (like organizations, locations, dates) and the relationships between them, presenting these insights in a structured way. This helps users grasp crucial information and connections without manually reading every document.
No commits in the last 6 months.
Use this if you need to automatically identify specific entities and their relationships within policy-related news articles or documents to build a knowledge base or streamline information retrieval.
Not ideal if your primary goal is general text summarization, sentiment analysis, or if your domain is outside of policy news.
Stars
11
Forks
1
Language
Python
License
—
Category
Last pushed
Apr 09, 2024
Commits (30d)
0
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