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semantic-relationship-extraction

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netik1020 / Concise-iPython-Notebooks-for-Deep-learning

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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.

deep-neural-networks text-classification word-embeddings snapshot image-processing text-generation autoencoder image-classification deeplearning text-processing image-segmentation semantic-relationship-extraction keras-neural-networks u-net bi-lstm-crf intent-classification attention-lstm inception-architecture unet-keras
  • Updated Aug 9, 2019
  • Jupyter Notebook

SoniaMola / SemanticsExtraction

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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.

nlp semantic-web spacy dbpedia wordnet semantic-relationship-extraction sparql-query stanza corenlp triple-extraction sparqlwrapper dbpedia-entities semantic-information
  • Updated Feb 28, 2022
  • Jupyter Notebook

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