Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T08:12:44.288Z Has data issue: false hasContentIssue false
  • English
  • Français

Revisiting the ontologising of semantic relation arguments in wordnet synsets

Published online by Cambridge University Press:  22 July 2015

HUGO GONÇALO OLIVEIRA Open the ORCID record for HUGO GONÇALO OLIVEIRA [Opens in a new window]  and
PAULO GOMES
HUGO GONÇALO OLIVEIRA
Affiliation:
CISUC, Department of Informatics Engineering, University of Coimbra, Polo 2, Pinhal de Marrocos, 3030-290 Coimbra, Portugal e-mail: hroliv@dei.uc.pt, pgomes@dei.uc.pt
PAULO GOMES
Affiliation:
CISUC, Department of Informatics Engineering, University of Coimbra, Polo 2, Pinhal de Marrocos, 3030-290 Coimbra, Portugal e-mail: hroliv@dei.uc.pt, pgomes@dei.uc.pt
Get access Rights & Permissions [Opens in a new window]

Abstract

Ontologising is the task of associating terms, in text, with an ontological representation of their meaning, in an ontology. In this article, we revisit algorithms that have previously been used to ontologise the arguments of semantic relations in a relationless thesaurus, resulting in a wordnet. For increased flexibility, the algorithms do not use the extraction context when selecting the most adequate synsets for each term argument. Instead, they exploit a term-based lexical network which can be established by knowledge extracted automatically, or obtained from the resource the relations are being ontologised to. On the latter idea, we made several experiments to conclude that the algorithms can be used both for wordnet creation and for their enrichment. Besides describing the algorithms with some detail, the aforementioned experiments, which target both English and Portuguese, and their results are reported and discussed.

Type
Articles
Information
Natural Language Engineering , Volume 22 , Issue 6 , November 2016 , pp. 819 - 848
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agichtein, E., and Gravano, L. 2000. Snowball: extracting relations from large plain-text collections. Proceedings of the 5th ACM International Conference on Digital Libraries, San Antonio, TX, USA: ACM, pp. 85–94.Google Scholar
Agirre, E., and Soroa, A. 2009. Personalizing PageRank for word sense disambiguation. Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics(EACL-2009). Athens, Greece: ACL Press, pp. 33–41.Google Scholar
Banerjee, S., and Pedersen, T. 2002. An adapted lesk algorithm for word sense disambiguation using WordNet. Proceedings of the 3rd International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2002). LNCS, vol. 2276, London, UK: Springer, pp. 136–145.Google Scholar
Barzilay, R., and Elhadad, M. 1997. Using lexical chains for text summarization. In Proceedings of the ACL/EACL Workshop on Intelligent Scalable Text Summarization(ISTS-1997), Madrid, Spain: ACL Press.Google Scholar
Bond, F., and Paik, K. 2012. A survey of wordnets and their licenses. In Proceedings of the 6th Global WordNet Conference(GWC-2012). Matsue, Japan: The Global WordNet Association.Google Scholar
Brin, S., and Page, L., 1998. The anatomy of a large-scale hypertextual web search engine. Computer Networks 30 (1–7): 107–117.Google Scholar
Caraballo, S. A. 1999. Automatic construction of a hypernym-labeled noun hierarchy from text. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics(ACL-1999), Maryland, USA: ACL Press, pp. 120–126.Google Scholar
Cuadros, M., and Rigau, G. 2008. KnowNet: building a large net of knowledge from the web. Proceedings of the 22nd International Conference on Computational Linguistics, (COLING-2008). vol. 1, Manchester, UK: ACL Press, pp. 161–168.Google Scholar
de Melo, G., and Weikum, G. 2009. Towards a universal wordnet by learning from combined evidence. Proceedings of the 18th ACM Conference on Information and Knowledge Management(CIKM-2009). Hong Kong, China: ACM Press, pp. 513–522.Google Scholar
de Paiva, V., Rademaker, A. and de Melo, G. 2012. OpenWordNet-PT: an open Brazilian WordNet for reasoning. In Proceedings of the 24th International Conference on Computational Linguistics. COLING (Demo Paper). Mumbai, India: The COLING 2012 Organizing Committee.Google Scholar
Dijkstra, E. W., 1959. A note on two problems in connexion with graphs. Numerische Mathematik 1 (1): 269–271.Google Scholar
Etzioni, O., Fader, A., Christensen, J., Soderland, S., and Mausam. 2011. Open information extraction: the second generation. Proceedings of 22nd International Joint Conference on Artificial Intelligence(IJCAI-2011). Barcelona, Spain: IJCAI/AAAI, pp. 3–10.Google Scholar
Fellbaum, C. (ed). 1998. WordNet: An Electronic Lexical Database (Language, Speech, and Communication). MIT Press.Google Scholar
Flati, T., and Navigli, R. 2013. SPred: large-scale harvesting of semantic predicates. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, ACL. Sofia, Bulgaria: ACL Press, pp. 1222–1232.Google Scholar
Gale, W. A., Church, K. W., and Yarowsky, D., 1992. One sense per discourse. In Proceedings of HLT’91 Workshop on Speech and Natural Language, Stroudsburg, PA, USA: ACL Press, pp. 233–237.Google Scholar
Gangemi, A., Guarino, N., Masolo, C., and Oltramari, A. 2010. Interfacing WordNet with DOLCE: towards OntoWordNet. In Ontology and the Lexicon: A Natural Language Processing Perspective, Chapter 3, pp. 36–52. Studies in Natural Language Processing. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Gonçalo Oliveira, H., and Gomes, P., 2012. Ontologising semantic relations into a relationless thesaurus. In Proceedings of 20th European Conference on Artificial Intelligence (ECAI-2012), Montpellier, France: IOS Press, pp. 915–916.Google Scholar
Gonçalo Oliveira, H., and Gomes, P., 2014. ECO and Onto.PT: a flexible approach for creating a Portuguese wordnet automatically. Language Resources and Evaluation 48 (2): 373–393.Google Scholar
Gonçalo Oliveira, H., Gomes, P., Santos, D., and Seco, N. 2008. PAPEL: a dictionary-based lexical ontology for Portuguese. In Proceedingsof the 8th International Conference on Computational Processing of the Portuguese Language (PROPOR-2008), vol. 5190, Aveiro, Portugal: Springer, pp. 31–40.Google Scholar
Harabagiu, S. M., and Moldovan, D. I. 2000. Enriching the WordNet taxonomy with contextual knowledge acquired from text. Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language. Cambridge, MA, USA: MIT Press, pp. 301–333.Google Scholar
Hearst, M. A. 1992. Automatic acquisition of hyponyms from large text corpora. Proceedings of 14th Conference on Computational Linguistics, (COLING-1992). Nantes, France: ACL Press, pp. 539–545.Google Scholar
Min, B., Shi, S., Grishman, R., and Lin, C.-Y. 2012. Ensemble semantics for large-scale unsupervised relation extraction. Proceedings of Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, (EMNLP-CoNLL-2012). Jeju, Korea: ACL Press, pp. 1027–1037.Google Scholar
Moldovan, D., and Novischi, A. 2002. Lexical chains for question answering. In Proceedings of the 19th International Conference on Computational Linguistics(COLING-2002). Taipei, Taiwan: ACL Press.Google Scholar
Moro, A., and Navigli, R. 2013. Integrating syntactic and semantic analysis into the open information extraction paradigm. Proceedings of the 23rd International Joint Conference on Artificial Intelligence(IJCAI), Beijing, China: AAAI Press, pp. 2148–2154.Google Scholar
Nakashole, N., Weikum, G., and Suchanek, F. 2012. PATTY: a taxonomy of relational patterns with semantic types. Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning(EMNLP-CoNLL-2012). Jeju, Korea: ACL Press, pp. 1135–1145.Google Scholar
Navigli, R., 2009. Word sense disambiguation: a survey. ACM Computing Surveys 41 (2): 1–69.Google Scholar
Navigli, R., and Ponzetto, S. P., 2012. BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial Intelligence 193 (December): 217–250.Google Scholar
Navigli, R., Velardi, P., Cucchiarelli, A., and Neri, F. 2004. Extending and enriching WordNet with OntoLearn. In Proceedings of the 2nd Global WordNet Conference(GWC-2004). Brno, Czech Republic: Masaryk University, pp. 279–284.Google Scholar
Pantel, P. 2005. Inducing ontological Co-occurrence vectors. In Proceedings of 43rd annual meeting of the Association for Computational Linguistics(ACL-2005). Ann Arbor, Michigan, USA: ACL Press, pp. 125–132.Google Scholar
Pantel, P., and Pennacchiotti, M. 2006. Espresso: leveraging generic patterns for automatically harvesting semantic relations. Proceedings of 21th International Conference on Computational Linguistics and 44th annual meeting of the Association for Computational Linguistics(COLING/ACL-2006). Sydney, Australia: ACL Press, pp. 113–120.Google Scholar
Pease, A., and Fellbaum, C. 2010. Formal ontology as interlingua: the SUMO and WordNet linking project and global WordNet linking project. Ontology and the Lexicon: A Natural Language Processing Perspective, Chapter 2, pp. 25–35. Studies in Natural Language Processing. Cambridge: Cambridge University Press.Google Scholar
Pennacchiotti, M., and Pantel, P. 2006. Ontologizing semantic relations. Proceedings of the 21th International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics(COLING/ACL-2006). Sydney, Australia: ACL Press, pp. 793–800.Google Scholar
Pustejovsky, J., Castaño, J. M., Zhang, J., Kotecki, M., and Cochran, B. 2002. Robust relational parsing over biomedical literature: extracting inhibit relations. In Pacific Symposium on Biocomputing, pp. 362–373. Singapore: World Scientific Publishing.Google Scholar
Resnik, P., 1995. Disambiguating noun groupings with respect to WordNet senses. In Proceedings of the 3rd Workshop on Very Large Corpora, Cambridge, Massachusetts, USA: MIT, pp. 54–68.Google Scholar
Soderland, S., and Mandhani, B., 2007. Moving from textual relations to ontologized relations. In Proceedings of AAAI Spring Symposium on Machine Reading, Menlo Park, California: AAAI Press, pp. 85–90.Google Scholar
Suchanek, F. M., Kasneci, G., and Weikum, G. 2007. YAGO: a core of semantic knowledge. Proceedings of the 16th International Conference on the World Wide Web(WWW-2007), Alberta, Canada: ACM Press, pp. 697–706.Google Scholar
Toral, A., Muñoz, R., and Monachini, M. 2008. Named entity WordNet. In Proceedings of the International Conference on Language Resources and Evaluation(LREC-2008). Marrakech, Morocco: ELRA.Google Scholar
Wiegand, M., Roth, B., and Klakow, D. 2012. Web-based relation extraction for the food domain. In Natural Language Processing and Information Systems, Proceedings of 17th International Conference on Applications of Natural Language to Information Systems (NLDB). LNCS, vol. 7337, Groningen, The Netherlands: Springer, pp. 222–227.Google Scholar