Summary of the paper

Title Mapping WordNet synsets to Wikipedia articles
Authors Samuel Fernando and Mark Stevenson
Abstract Lexical knowledge bases (LKBs), such as WordNet, have been shown to be useful for a range of language processing tasks. Extending these resources is an expensive and time-consuming process. This paper describes an approach to address this problem by automatically generating a mapping from WordNet synsets to Wikipedia articles. A sample of synsets has been manually annotated with article matches for evaluation purposes. The automatic methods are shown to create mappings with precision of 87.8% and recall of 46.9%. These mappings can then be used as a basis for enriching WordNet with new relations based on Wikipedia links. The manual and automatically created data is available online.
Topics Word Sense Disambiguation, Document Classification, Text categorisation, Lexicon, lexical database
Full paper Mapping WordNet synsets to Wikipedia articles
Bibtex @InProceedings{FERNANDO12.232,
  author = {Samuel Fernando and Mark Stevenson},
  title = {Mapping WordNet synsets to Wikipedia articles},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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