Lexical and Semantic Resources for NLP: From Words to Meanings

  • Anna Lisa Gentile
  • Pierpaolo Basile
  • Leo Iaquinta
  • Giovanni Semeraro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5179)


A user expresses her information need through words with a precise meaning, but from the machine point of view this meaning does not come with the word. A further step is needful to automatically associate it to the words. Techniques that process human language are required and also linguistic and semantic knowledge, stored within distinct and heterogeneous resources, which play an important role during all Natural Language Processing (NLP) steps. Resources management is a challenging problem, together with the correct association between URIs coming from the resources and meanings of the words.

This work presents a service that, given a lexeme (an abstract unit of morphological analysis in linguistics, which roughly corresponds to a set of words that are different forms of the same word), returns all syntactic and semantic information collected from a list of lexical and semantic resources. The proposed strategy consists in merging data with origin from stable resources, such as WordNet, with data collected dynamically from evolving sources, such as the Web or Wikipedia. That strategy is implemented in a wrapper to a set of popular linguistic resources that provides a single point of access to them, in a transparent way to the user, to accomplish the computational linguistic problem of getting a rich set of linguistic and semantic annotations in a compact way.


Natural Language Processing Name Entity Recognition Word Sense Disambiguation Entity Recognition Language Resource 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Proceedings of the 2001 ACM CIKM International Conference on Information and Knowledge Management. ACM Press, New York (November 5-10, 2001)Google Scholar
  2. 2.
    Language resource management –Lexical markup framework (LMF) (March 2008),
  3. 3.
    Agirre, E., de Lacalle Lekuona, O.L.: Publicly available topic signatures for all wordnet nominal senses. In: The 4rd International Conference on Languages Resources and Evaluations (LREC), Lisbon, Portugal (2004)Google Scholar
  4. 4.
    Bunescu, R., Pasca, M.: Using encyclopedic knowledge for named entity disambiguation. In: Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2006), Trento, Italy, pp. 9–16 (April 2006)Google Scholar
  5. 5.
    Ghani, R., Jones, R., Mladenic, D.: Mining the web to create minority language corpora. In: CIKM [1], pp. 279–286Google Scholar
  6. 6.
    Kazama, J., Torisawa, K.: Exploiting wikipedia as external knowledge for named entity recognition. In: Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 698–707 (2007)Google Scholar
  7. 7.
    Kilgarriff, A., Grefenstette, G.: Introduction to the special issue on the web as corpus. Computational Linguistics 29(3), 333–348 (2003)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Kwok, C.C.T., Etzioni, O., Weld, D.S.: Scaling question answering to the web. ACM Trans. Inf. Syst. 19(3), 242–262 (2001)CrossRefGoogle Scholar
  9. 9.
    Magnini, B., Cavaglià, G.: Integrating subject field codes into wordnet. In: 2nd International Conference on Language Resources and Evaluation (LREC 2000), pp. 1413–1418 (2000)Google Scholar
  10. 10.
    Magnini, B., Negri, M., Prevete, R., Tanev, H.: Is it the right answer? exploiting web redundancy for answer validation. In: ACL, pp. 425–432 (2002)Google Scholar
  11. 11.
    Miller, G.: Wordnet: An on-line lexical database. International Journal of Lexicography 3(4) (1990) (Special Issue) Google Scholar
  12. 12.
    Navigli, R.: Meaningful clustering of senses helps boost word sense disambiguation performance. In: Annual Meeting of the Association for Computational Linguistics joint with the 21st International Conference on Computational Linguistics (COLING-ACL 2006), pp. 105–112 (2006)Google Scholar
  13. 13.
    Ponzetto, S.P., Strube, M.: Exploiting semantic role labeling, wordnet and wikipedia for coreference resolution. In: Moore, R.C., Bilmes, J.A., Chu-Carroll, J., Sanderson, M. (eds.) HLT-NAACL. The Association for Computational Linguistics (2006)Google Scholar
  14. 14.
    Prévot, L., Borgo, S., Oltramari, A.: Interfacing ontologies and lexical resources. In: Proceedings of OntoLex 2005 - Ontologies and Lexical Resources, Jeju Island, Republic of Korea (October 15, 2005)Google Scholar
  15. 15.
    Radev, D.R., Qi, H., Zheng, Z., Blair-Goldensohn, S., Zhang, Z., Fan, W., Prager, J.M.: Mining the web for answers to natural language questions. In: CIKM [1], pp. 143–150Google Scholar
  16. 16.
    Rosso, P., y Gómez, M.M., Buscaldi, D., Pancardo-Rodríguez, A., Pineda, L.V.: Two Web-Based Approaches for Noun Sense Disambiguation. In: Gelbukh, A. (ed.) CICLing 2005. LNCS, vol. 3406, pp. 267–279. Springer, Heidelberg (2005)Google Scholar
  17. 17.
    Ruiz-Casado, M., Alfonseca, E., Castells, P.: From wikipedia to semantic relationships: a semi-automated annotation approach. In: Völkel, M., Schaffert, S. (eds.) SemWiki. CEUR Workshop Proceedings,, vol. 206 (2006)Google Scholar
  18. 18.
    Strapparava, C., Valitutti, A.: Wordnet-affect: an affective extension of wordnet. In: 4th International Conference on Language Resources and Evaluation (LREC 2004), pp. 1083–1086 (2004)Google Scholar
  19. 19.
    Strube, M., Ponzetto, S.P.: Wikirelate! computing semantic relatedness using wikipedia. In: AAAI. AAAI Press, Menlo Park (2006)Google Scholar
  20. 20.
    Terra, E.L., Clarke, C.L.A.: Frequency estimates for statistical word similarity measures. In: HLT-NAACL 2003 (2003)Google Scholar
  21. 21.
    Toral, A., Munoz, R.: A proposal to automatically build and maintain gazetteers for Named Entity Recognition by using Wikipedia. In: EACL 2006 (2006)Google Scholar
  22. 22.
    Turney, P.D.: Mining the web for synonyms: Pmi-ir versus lsa on toefl. In: Raedt, L.D., Flach, P. (eds.) ECML 2001. LNCS (LNAI), vol. 2167, pp. 491–502. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  23. 23.
    Zesch, T., Gurevych, I., Mühlhäuser, M.: Analyzing and accessing wikipedia as a lexical semantic resource. In: Biannual Conference of the Society for Computational Linguistics and Language Technology (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Anna Lisa Gentile
    • 1
  • Pierpaolo Basile
    • 1
  • Leo Iaquinta
    • 1
  • Giovanni Semeraro
    • 1
  1. 1.Dipartimento di InformaticaUniversità di BariBariItalia

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