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semantic-relationship-extraction

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Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

  • Updated Aug 9, 2019
  • Jupyter Notebook

The aim of the project is to extract from Natural Language relevant semantic informations. The input text is divided into triples (Subject - Relation - Object). WordNet here is used to get the meaning of relation and DBpedia is used to extract information from subject and object.

  • Updated Feb 28, 2022
  • Jupyter Notebook

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