Abstract
Computational semantics and logic-based controlled natural languages (CNL) do not address systematically the word sense disambiguation problem of content words, i.e., they tend to interpret only some functional words that are crucial for construction of discourse representation structures. We show that micro-ontologies and multi-word units allow integration of the rich and polysemous multi-domain background knowledge into CNL thus providing interpretation for the content words. The proposed approach is demonstrated by extending the Attempto Controlled English (ACE) with polysemous and procedural constructs resulting in a more natural CNL named PAO covering narrative multi-domain texts.
Keywords
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.
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
Schwitter, R., Kaljurand, K., Cregan, A., Dolbear, C., Hart, G.: A Comparison of three Controlled Natural Languages for OWL 1.1. In: 4th International OWLED Workshop (2008)
Clark, P., Harrison, P., Jenkins, T., Thompson, J., Wojcik, R.H.: Acquiring and Using World Knowledge Using a Restricted Subset of English. In: 18th International FLAIRS Conference, pp. 506–511 (2005)
Fuchs, N.E., Kaljurand, K., Schneider, G.: Attempto Controlled English Meets the Challenges of Knowledge Representation, Reasoning, Interoperability and User Interfaces. In: 19th International FLAIRS Conference (2006)
Pustejovsky, J.: Type Construction and the Logic of Concepts. In: Bouillon, P., Busa, F. (eds.) The Language of Word Meaning. Cambridge University Press, Cambridge (2001)
Ravin, Y., Leacock, C.: Polysemy. Oxford University Press, Oxford (2000)
Leary, D.E. (ed.): Metaphors in the history of psychology. Cambridge University Press, Cambridge (1994)
Magnini, B., Strapparava, C., Pezzulo, G., Gliozzo, A.: The role of domain information in word sense disambiguation. Natural Language Engineering 8(4), 359–373 (2002)
Web Ontology Language (OWL). W3C Recommendation (2009), http://www.w3.org/TR/owl2-overview/
Rinaldi, F., Dowdall, J., Hess, M., Molla, D., Schwitter, R., Kaljurand, K.: Knowledge-Based Question Answering. In: Palade, V., Howlett, R.J., Jain, L. (eds.) KES 2003. LNCS (LNAI), vol. 2773, pp. 785–792. Springer, Heidelberg (2003)
Wilks, Y., Barnden, J., Wang, J.: Your metaphor or mine: belief ascription and metaphor interpretation. In: 12th International Joint Conference on Artificial Intelligence, pp. 945–950 (1991)
Lenat, D.: Cyc: A Large-Scale Investment in Knowledge Infrastructure. Communications of the ACM 38(11), 33–38 (1995)
Fillmore, C.J., Johnson, C.R., Petruck, M.R.L.: Background to FrameNet. International Journal of Lexicography 16, 235–250 (2003)
Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, New York (2007)
Banek, M., Vrdoljak, B., Tjoa, A.M.: Word Sense Disambiguation as the Primary Step of Ontology Integration. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds.) DEXA 2008. LNCS, vol. 5181, pp. 65–72. Springer, Heidelberg (2008)
Schwitter, R.: Creating and Querying Linguistically Motivated Ontologies. In: Knowledge Representation Ontology Workshop, Conference in Research and Practice in Information Technology, vol. 90, pp. 71–80 (2008)
Kaljurand, K., Fuchs, N.E.: Verbalizing OWL in Attempto Controlled English. In: 3rd International OWLED Workshop (2007)
SPARQL 1.1 Query and Unpdate Language for RDF. W3C Working Draft (2009), http://www.w3.org/2009/sparql/wiki/Main_Page
Ontology Definition Metamodel. OMG Adopted Specification (2009), http://www.omg.org/docs/ptc/07-09-09.pdf
PDDL - The Planning Domain Definition Language. Technical report, Yale Center for Computational Vision and Control (1998), http://www.cs.yale.edu/homes/dvm/
Erk, K., Pado, S.: Shalmaneser - a flexible toolbox for semantic role assignment. In: 5th International LREC Conference (2006)
Johansson, R., Nugues, P.: Comparing dependency and constituent syntax for frame-semantic analysis. In: 6th International LREC Conference (2008)
Johansson, R., Berglund, A., Danielsson, M., Nugues, P.: Automatic text-to-scene conversion in the traffic accident domain. In: 19th International Joint Conference on Artificial Intelligence, pp. 1073–1078 (2005)
Schubert, L.K., Hwang, C.H.: Episodic Logic meets Little Red Riding Hood: A comprehensive, natural representation for language understanding. In: Iwanska, L., Shapiro, S.C. (eds.) Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language, pp. 111–174. MIT/AAAI Press, Cambridge/Menlo Park (2000)
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
Gruzitis, N., Barzdins, G. (2010). Polysemy in Controlled Natural Language Texts. In: Fuchs, N.E. (eds) Controlled Natural Language. CNL 2009. Lecture Notes in Computer Science(), vol 5972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14418-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-14418-9_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14417-2
Online ISBN: 978-3-642-14418-9
eBook Packages: Computer ScienceComputer Science (R0)