hrlics/SemDI
[EMNLP 2024] Advancing Event Causality Identification via Heuristic Semantic Dependency Inquiry Network
This project helps identify cause-and-effect relationships between events mentioned in text documents. You provide a piece of text and two events from that text, and it determines if one event caused the other, or if they are unrelated. This is useful for researchers and analysts who need to understand complex interactions and dependencies within written content.
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Use this if you need to automatically discover causal links between specific actions or occurrences described in various texts, like news articles or reports.
Not ideal if you're looking for a tool to extract general sentiment or broad topics from text, rather than specific causal event pairs.
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13
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1
Language
Jupyter Notebook
License
MIT
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Last pushed
Oct 13, 2025
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