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  1. OpenNLP
  2. OPENNLP-758

Unsupervised WSD techniques

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Details

    • New Feature
    • Status: Open
    • Major
    • Resolution: Unresolved
    • None
    • None
    • wsd

    Description

      The objective of Word Sense Disambiguation (WSD) is to determine which sense of a word is meant in a particular context. Therefore, WSD is a classification task, where the classes are the different senses of the ambiguous word.

      Different techniques are proposed in the academic literature, which fall mainly into two categories: Supervised and Unsupervised.

      For this component, we focus on unsupervised techniques: these methods are based on unlabeled data, and do not exploit any manually tagged data.

      The object of this project is to create a WSD solution (for English) that implements some unsupervised techniques. For example:

      • Context Clustering
      • Word Clustering
      • Cooccurrence Graphs
      • Overlap of Sense Definitions
      • Selectional Preferences
      • Structural Approaches
      • Etc.

      Attachments

        1. updates_and_fix_new_datareaders.patch
          82 kB
          Anthony Beylerian
        2. opennlp-tools-disambiguator.patch
          54 kB
          Anthony Beylerian
        3. lesk_params_source.patch
          6 kB
          Anthony Beylerian
        4. lesk_parameters.patch
          68 kB
          Anthony Beylerian
        5. cleanup.patch
          79 kB
          Anthony Beylerian

        Activity

          People

            beylerian Anthony Beylerian
            mondher Mondher Bouazizi
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            Dates

              Created:
              Updated: