Summary of the paper

Title Huge Automatically Extracted Training-Sets for Multilingual Word SenseDisambiguation
Authors Tommaso Pasini, Francesco Elia and Roberto Navigli
Abstract We release to the community six large-scale sense-annotated datasets in multiple language to pave the way for supervised multilingual Word Sense Disambiguation. Our datasets cover all the nouns in the English WordNet and their translations in other languages for a total of millions of sense-tagged sentences. Experiments prove that these corpora can be effectively used as training sets for supervised WSD systems, surpassing the state of the art for low-resourced languages and providing competitive results for English, where manually annotated training sets are available. The data is available at trainomatic.org.
Topics Multilinguality, Word Sense Disambiguation, Semantics
Full paper Huge Automatically Extracted Training-Sets for Multilingual Word SenseDisambiguation
Bibtex @InProceedings{PASINI18.731,
  author = {Tommaso Pasini and Francesco Elia and Roberto Navigli},
  title = "{Huge Automatically Extracted Training-Sets for Multilingual Word SenseDisambiguation}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
  }
Powered by ELDA © 2018 ELDA/ELRA