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Extracts a latent knowledge graph from text and index/query it in elasticsearch or solr

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Skipchunk

Pypi

Travis build status

Documentation Status

Easy natural language concept search for the masses.

Out of the box it provides a hassle-free autosuggest for any corpus from scratch, and latent knowledge graph extraction and exploration.

Install

pip install skipchunk
python -m spacy download 'en_core_web_lg'
python -m nltk.downloader wordnet

You also need to have Solr or Elasticsearch installed and running somewhere! The current supported version is 8.4.1, but it might work on other versions.

Use It!

See the ./example/ folder for an end-to-end OSC blog load and query

Features

  • Identifies all the noun phrases and verb phrases in a corpus
  • Indexes these phrases in Solr for a really good out-of-the-box autosuggest
  • Structures the phrases as a graph so that concept-relationship-concept can be easily found
  • Keeps enriched content ready for reindexing

Credits

Developed by Max Irwin, OpenSourceConnections https://opensourceconnections.com

All the blog posts contained in the example directory are copyright OpenSource Connections, and may not be redistributed without permission