vene/marseille
Mining Argument Structures with Expressive Inference (Linear and LSTM Engines)
This project helps researchers and computational linguists analyze written text to identify argumentative statements and understand how they relate to each other. It takes raw text documents as input and outputs classifications of argumentative propositions and the supporting connections between them. This is useful for anyone studying the structure of arguments within natural language.
No commits in the last 6 months.
Use this if you need to automatically identify the different parts of an argument in a document and understand their logical relationships.
Not ideal if you're looking for a simple, out-of-the-box application for general text analysis or sentiment analysis.
Stars
66
Forks
29
Language
Python
License
BSD-3-Clause
Category
Last pushed
Aug 01, 2017
Commits (30d)
0
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