THU-KEG/OmniEvent
A comprehensive, unified and modular event extraction toolkit.
This project helps you automatically pinpoint specific events and their details within large volumes of text, extracting key information like who did what, when, and where. It takes raw English or Chinese text documents and outputs structured event data, showing you recognized events, their triggers, and associated arguments. This tool is designed for data analysts, researchers, or anyone needing to extract factual events from unstructured text.
405 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to systematically identify and categorize real-world events and their crucial attributes from written content, such as news articles, reports, or social media posts.
Not ideal if your goal is general text summarization, sentiment analysis, or if you primarily work with non-textual data.
Stars
405
Forks
38
Language
Python
License
MIT
Category
Last pushed
Dec 18, 2024
Commits (30d)
0
Dependencies
9
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