Summary of the paper

Title Boosting the Coverage of a Semantic Lexicon by Automatically Extracted Event Nominalizations
Authors Kata Gábor, Marianna Apidianaki, Benoît Sagot and Éric Villemonte de la Clergerie
Abstract In this article, we present a distributional analysis method for extracting nominalization relations from monolingual corpora. The acquisition method makes use of distributional and morphological information to select nominalization candidates. We explain how the learning is performed on a dependency annotated corpus and describe the nominalization results. Furthermore, we show how these results served to enrich an existing lexical resource, the WOLF (Wordnet Libre du Franc¬łais). We present the techniques that we developed in order to integrate the new information into WOLF, based on both its structure and content. Finally, we evaluate the validity of the automatically obtained information and the correctness of its integration into the semantic resource. The method proved to be useful for boosting the coverage of WOLF and presents the advantage of filling verbal synsets, which are particularly difficult to handle due to the high level of verbal polysemy.
Topics Acquisition, Lexicon, lexical database, Ontologies
Full paper Boosting the Coverage of a Semantic Lexicon by Automatically Extracted Event Nominalizations
Bibtex @InProceedings{GBOR12.839,
  author = {Kata Gábor and Marianna Apidianaki and Benoît Sagot and Éric Villemonte de la Clergerie},
  title = {Boosting the Coverage of a Semantic Lexicon by Automatically Extracted Event Nominalizations},
  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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