swabhs/open-sesame
A frame-semantic parsing system based on a softmax-margin SegRNN.
This tool helps linguistics researchers and natural language processing (NLP) practitioners automatically analyze the meaning of sentences by identifying "frames" (like 'Commerce_buy') and their associated "frame elements" (like 'Buyer', 'Goods', 'Seller'). You input raw text sentences, and it outputs a detailed breakdown of the semantic roles played by words and phrases, based on the FrameNet database. This is for anyone needing to semantically annotate large volumes of text.
240 stars. No commits in the last 6 months.
Use this if you need to automatically extract and label the underlying semantic structure of sentences, identifying who did what to whom, with what, where, and when, for linguistics research or NLP applications.
Not ideal if you're looking for a simple keyword extractor or sentiment analysis tool, or if you don't require the deep semantic understanding provided by FrameNet.
Stars
240
Forks
69
Language
Python
License
Apache-2.0
Category
Last pushed
May 07, 2022
Commits (30d)
0
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