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KNEWS: Using Logical and Lexical Semantics to Extract Knowledge from Natural Language

Valerio Basile 1, 2 Elena Cabrio 1, 2 Claudia Schon 3
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : We present KNEWS, a pipeline of NLP tools that accepts natural language text as input and outputs knowledge in a machine-readable format. The tool outputs frame-based knowledge as RDF triples or XML, including the word-level alignment with the surface form, as well as first-order logical formulae. KNEWS is freely available for download. Moreover, thanks to its versatility, KNEWS has already been employed for a number of different applications for information extraction and automatic reasoning.
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Submitted on : Friday, October 28, 2016 - 1:30:56 PM
Last modification on : Tuesday, December 7, 2021 - 4:10:18 PM


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  • HAL Id : hal-01389390, version 1



Valerio Basile, Elena Cabrio, Claudia Schon. KNEWS: Using Logical and Lexical Semantics to Extract Knowledge from Natural Language. Proceedings of the European Conference on Artificial Intelligence (ECAI) 2016 conference, Aug 2016, The Hague, Netherlands. ⟨hal-01389390⟩



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