Abstract
Detecting error in text is a difficult task. Current methods use a domain ontology to identify elements in the text that contradicts domain knowledge. Yet, these methods require manually defining the type of errors that are expected to be found in the text before applying them. In this paper we propose a new approach that uses logic reasoning to detect errors in a statement from text online. Such approach applies Information Extraction to transform text into a set of logic clauses. The logic clauses are incorporated into the domain ontology to determine if it contradicts the ontology or not. If the statement contradicts the domain ontology, then the statement is incorrect with respect to the domain knowledge. We have evaluated our proposed method by applying it to a set of written summaries from the domain of Ecosystems. We have found that this approach, although depending on the quality of the Information Extraction output, can identify a significant amount of errors. We have also found that modeling elements of the ontology (i.e., property domain and range) likewise affect the capability of detecting errors.
Chapter PDF
Similar content being viewed by others
References
Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., Ant Peter, D.L.M., Patel-Schneider, F., Stein, L.A.: OWL Web Ontology Language, http://www.w3.org/TR/owl-ref/
Blessing, A., Schütze, H.: Crosslingual distant supervision for extracting relations of different complexity. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012, pp. 1123–1132 (2012)
Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, pp. 1535–1545 (2011)
Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G.: Ontology change: Classification and survey. The Knowledge Engineering Review 23(02), 117–152 (2008)
Gutierrez, F., Dou, D., Fickas, S., Griffiths, G.: Providing Grades and Feedback for Student Summaries by Ontology-based Information Extraction. In: Proceedings of the 21st ACM Conference on Information and Knowledge Management, CIKM 2012, pp. 1722–1726 (2012)
Gutierrez, F., Dou, D., Fickas, S., Martini, A., Zong, H.: Hybrid Ontology-based Information Extraction for Automated Text Grading. In: Proceedings of the 12th IEEE International Conference on Machine Learning and Applications, ICMLA 2013, pp. 359–364 (2013)
Haase, P., Stojanovic, L.: Consistent evolution of OWL ontologies. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 182–197. Springer, Heidelberg (2005)
Haase, P., Völker, J.: Ontology learning and reasoning — dealing with uncertainty and inconsistency. In: da Costa, P.C.G., d’Amato, C., Fanizzi, N., Laskey, K.B., Laskey, K.J., Lukasiewicz, T., Nickles, M., Pool, M. (eds.) URSW 2005 - 2007. LNCS (LNAI), vol. 5327, pp. 366–384. Springer, Heidelberg (2008)
Hearst, M.A.: Automatic Acquisition of Hyponyms from Large Text Corpora. In: Proceedings of the Fourteenth Conference on Computational Linguistics, COLING 1992, pp. 539–545 (1992)
Horridge, M., Parsia, B., Sattler, U.: Explaining inconsistencies in OWL ontologies. In: Godo, L., Pugliese, A. (eds.) SUM 2009. LNCS, vol. 5785, pp. 124–137. Springer, Heidelberg (2009)
Horrocks, I., Patel-Schneider, P.F.: Reducing OWL entailment to description logic satisfiability. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 17–29. Springer, Heidelberg (2003)
Huang, Z., van Harmelen, F., Teije, A.t.: Reasoning with inconsistent ontologies. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI 2005, pp. 454–459 (2005)
Landauer, T.K., Laham, D., Foltz, P.W.: Learning human-like knowledge by singular value decomposition: a progress report. In: Proceedings of the 1997 Conference on Advances in Neural Information Processing Systems 10, NIPS 1997, pp. 45–51 (1998)
Lin, C.-Y.: Rouge: a package for automatic evaluation of summaries. In: Workshop on Text Summarization Branches Out, pp. 25–26 (2004)
Mausam, Schmitz, M., Soderland, S., Bart, R., Etzioni, O.: Open language learning for information extraction. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2012, pp. 523–534 (2012)
Miller, G.A.: Wordnet: A lexical database for english. Communications of the ACM 38, 39–41 (1995)
Mintz, M., Bills, S., Snow, R., Jurafsky, D.: Distant supervision for relation extraction without labeled data. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, ACL 2009, pp. 1003–1011 (2009)
Motik, B., Shearer, R., Horrocks, I.: Hypertableau Reasoning for Description Logics. Journal of Artificial Intelligence Research 36, 165–228 (2009)
Reiter, R.: A theory of diagnosis from first principles. Artificial Intelligence 32(1), 57–95 (1987)
Ritter, A., Downey, D., Soderland, S., Etzioni, O.: It’s a contradiction—no, it’s not: A case study using functional relations. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, pp. 11–20. Association for Computational Linguistics, Stroudsburg (2008)
Schlobach, S., Cornet, R.: Non-standard reasoning services for the debugging of description logic terminologies. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI 2003, pp. 355–362 (2003)
Schlobach, S., Huang, Z., Cornet, R., van Harmelen, F.: Debugging incoherent terminologies. Journal of Automated Reasoning 39(3), 317–349 (2007)
Sohlberg, M., Griffiths, G., Fickas, S.: The effect of electronically delivered strategies on reading after mild-moderate acquired brain injury. American Journal of Speech-Language Pathology (November 2011) (in review)
Wimalasuriya, D.C., Dou, D.: Ontology-based information extraction: An introduction and a survey of current approaches. Journal of Information Science 36, 306–323 (2010)
Wu, F., Weld, D.S.: Autonomously semantifying wikipedia. In: Proceedings of the 16th ACM Conference on Information and Knowledge Management, CIKM 2007, pp. 41–50 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gutiererz, F., Dou, D., Fickas, S., Griffiths, G. (2014). Online Reasoning for Ontology-Based Error Detection in Text. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2014 Conferences. OTM 2014. Lecture Notes in Computer Science, vol 8841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45563-0_34
Download citation
DOI: https://doi.org/10.1007/978-3-662-45563-0_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45562-3
Online ISBN: 978-3-662-45563-0
eBook Packages: Computer ScienceComputer Science (R0)