Abstract
In a question answering system, users always prefer entering queries in natural language and not being constrained by a rigorous grammar. This paper proposes a syntax-free method for natural language query understanding that is robust to ill-formed questions. Nested conceptual graphs are defined as a formal target language to represent not only simple queries, but also connective, superlative, and counting queries. The method exploits knowledge of an ontology to recognize entities and determine their relations in a query. With smooth mapping to and from natural language, conceptual graphs simplify conversion rules from natural language queries and can be easily converted to other formal query languages. Experimental results of the method on the QA track datasets of TREC 2002 and TREC 2007 are presented and discussed.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Berners-Lee, T.: Conceptual Graphs and the Semantic Web, http://www.w3.org/DesignIssues/CG.html (Initially created: January 2001, Last change: April 2008)
Cao, T.H., Cao, T.D., Tran, T.L.: A Robust Ontology-Based Method for Translating Natural Language Queries to Conceptual Graphs. In: Domingue, J., Anutariya, C. (eds.) ASWC 2008. LNCS, vol. 5367, pp. 479–492. Springer, Heidelberg (2008)
Cimiano, P., Haase, P., Heizmann, J.: Porting Natural Language Interfaces between Domains An Experimental User Study with the ORAKEL System. In: Proceedings of the 12th ACM International Conference on Intelligent User Interfaces, pp. 180–189 (2007)
Cunningham, H., et al.: Developing Language Processing Components with GATE Version 3 (a User Guide). University of Sheffield (2006)
Dill, S., et al.: SemTag and Seeker: Bootstrapping the Semantic Web via Automated Semantic Annotation. In: Proceedings of the 12th International Conference on the World Wide Web, pp. 178–186 (2003)
Hensman, S., Dunnion, J.: Using Linguistic Resources to Construct Conceptual Graph Representation of Texts. In: Sojka, P., Kopeček, I., Pala, K. (eds.) TSD 2004. LNCS (LNAI), vol. 3206, pp. 81–88. Springer, Heidelberg (2004)
Kaufmann, E., Bernstein, A., Fischer, L.: NLP-Reduce: A “Nave” but Domain-Independent Natural Language Interface for Querying Ontologies. In: Demo-Paper at the 4th European Semantic Web Conference, pp. 1–2 (2007)
Kiryakov, A., Popov, B., Terziev, I., Manov, D., Ognyanoff, D.: Semantic Annotation, Indexing, and Retrieval. Journal of Web Semantics 2 (2005)
Lei, Y., Uren, V., Motta, E.: Semsearch: A Search Engine for the Semantic Web. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 238–245. Springer, Heidelberg (2006)
Nelken, R., Francez, N.: Querying Temporal Databases Using Controlled Natural Language. In: Proceedings of the 18th Conference on Computational Linguistics, pp. 1076–1080 (2000)
Nyberg, E.H., Mitamura, T.: Controlled Language and Knowledge-Based Machine Translation: Principles and Practice. In: Proceedings of the 1st International Workshop on Controlled Language Applications, pp. 74–83 (1996)
Ogden, W.C., Bernick, P.: Using Natural Language Interfaces. In: Helander, M., Landauer, T.K., Prabhu, P. (eds.) Handbook of Human-Computer Interaction, pp. 137–162. Elsevier Science, Amsterdam (1997)
Sowa, J.F.: Conceptual Structures Information Processing in Mind and Machine. Addison-Wesley Publishing Company, Reading (1984)
Sowa, J.F.: Matching Logical Structure to Linguistic Structure. In: Houser, N., Roberts, D.D., Van Evra, J. (eds.) Studies in the Logic of Charles Sanders Peirce, pp. 418–444. Indiana University Press (1997)
Tablan, V., Damljanovic, D., Bontcheva, K.: A Natural Language Query Interface to Structured Information. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS (LNAI), vol. 5021, pp. 361–375. Springer, Heidelberg (2008)
Yao, H., Etzkorn, L.: Conversion from the Conceptual Graph (CG) Model to the Resource Description Framework (RDF) Model. In: Contributions of the 12th International Conference on Conceptual Structures, pp. 98–114 (2004)
Zhang, L., Yu, Y.: Learning to Generate CGs for Domain Specific Sentences. In: Delugach, H.S., Stumme, G. (eds.) ICCS 2001. LNCS (LNAI), vol. 2120, pp. 44–57. Springer, Heidelberg (2001)
Zhu, J., Uren, V., Motta, E.: ESpotter: Adaptive Named Entity Recognition for Web Browsing. In: Althoff, K.-D., Dengel, A.R., Bergmann, R., Nick, M., Roth-Berghofer, T.R. (eds.) WM 2005. LNCS (LNAI), vol. 3782, pp. 518–529. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cao, T.H., Mai, A.H. (2010). Ontology-Based Understanding of Natural Language Queries Using Nested Conceptual Graphs. In: Croitoru, M., Ferré, S., Lukose, D. (eds) Conceptual Structures: From Information to Intelligence. ICCS 2010. Lecture Notes in Computer Science(), vol 6208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14197-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-14197-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14196-6
Online ISBN: 978-3-642-14197-3
eBook Packages: Computer ScienceComputer Science (R0)