Knowledge Extraction With Semantics

KNEWS is a composite tool that bridges semantic parsing (using C&C tools and Boxer), word sense disambiguation (using UKB or Babelfy) and entity linking (using Babelfy or DBpedia Spotlight) to produce a unified, LOD-compliant abstract representation of meaning.

KNEWS can produce several kinds of output:

1. Frame instances, based on the FrameBase scheme
2. Word-aligned semantics, based on lexicalized Discourse Representation Graphs)
3. First-order logic formulae with WordNet synsets and DBpedia ids as symbols

The source code of KNEWS is freely available at https://github.com/ valeriobasile/learningbyreading.

Contact the author: valerio[dot]basile[at]inria[anotherdot]fr

The demo is temporarily offline while I migrate KnEWS from Python 2 to Python3.