Abstract
We present a two-layer OWL ontology-based Knowledge Base (KB) that allows for flexible content selection and discourse structuring in Natural Language text Generation (NLG) and discuss its use for these two tasks. The first layer of the ontology contains an application-independent base ontology. It models the domain and was not designed with NLG in mind. The second layer, which is added on top of the base ontology, models entities and events that can be inferred from the base ontology, including inferable logico-semantic relations between individuals. The nodes in the KB are weighted according to learnt models of content selection, such that a subset of them can be extracted. The extraction is done using templates that also consider semantic relations between the nodes and a simple user profile. The discourse structuring submodule maps the semantic relations to discourse relations and forms discourse units to then arrange them into a coherent discourse graph. The approach is illustrated and evaluated on a KB that models the First Spanish Football League.
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References
Barzilay, R., Lapata, M.: Collective content selection for concept-to-text generation. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (2005)
Bohnet, B., Wanner, L.: Open Source Graph Transducer Interpreter and Grammar Development Environment. In: Proceedings of the Seventh Conference on International Language Resources and Evaluation, LREC 2010 (2010)
Bontcheva, K., Wilks, Y.: Automatic Report Generation from Ontologies: The MIAKT Approach. In: Meziane, F., Métais, E. (eds.) NLDB 2004. LNCS, vol. 3136, pp. 324–335. Springer, Heidelberg (2004)
Demir, S., Carberry, S., McCoy, K.F.: A Discourse-Aware Graph-Based Content-Selection Framework. In: Proceedings of the International Natural Language Generation Conference (2010)
O’Donnell, M., Mellish, C., Oberlander, J., Knott, A.: ILEX: An architecture for a dynamic hypertext generation system. Natural Language Engineering 7, 225–250 (2001)
Duboue, P.A., McKeown, K.R.: Statistical Acquisition of Content Selection Rules for Natural Language Generation. In: Proceedings of Empirical Methods for Natural Language Processing (EMNLP), pp. 121–128 (2003)
Dukle, K.: A Prototype Query-Answering Engine Using Semantic Reasoning. Master Thesis. University of South Carolina (2003)
Galanis, D., Androutsopoulos, I.: Generating Multilingual Descriptions from Linguistically Annotated OWL Ontologies: the NaturalOWL System. In: Proceedings of the 11th European Workshop on Natural Language Generation (ENLG 2007). Schloss Dagstuhl, Germany (2007)
Hovy, E.H.: Automated Discourse Generation Using Discourse Structure Relations. Artificial Intelligence 63(1-2), 341–386 (1993)
Kelly, C., Copestake, A., Karamanis, N.: Investigating content selection for language generation using machine learning. In: Proceedings of the 12th European Workshop on Natural Language Generation, pp. 130–137 (2009)
Kittredge, R., Korelsky, T., Rambow, O.: On the need for domain communication knowledge. Computational Intelligence 7(4), 305–314 (1991)
Lenat, D.B.: CYC: a large-scale investment in knowledge infrastructure. Communications of the ACM 38(11), 33–38 (1995)
Mann, W., Thompson, S.: Rhetorical Structure Theory: Toward a functional thoery of text organization. Text 8(3) (1988)
Mellish, C., Dale, R.: Evaluation in the Context of Natural Language Generation. Computer Speech and Language 12, 349–373 (1998)
Mellish, C., Pan, J.: Natural Language Directed Inference from Ontologies. Artificial Intelligence 172(10), 1285–1315 (2008)
Reiter, E.: An Architecture for Data-to-Text Systems. In: Proceedings of ENLG 2007, pp. 97–104 (2007)
Schapire, R.E., Singer, Y.: BoosTexter: A boosting-based system for text categorization. Machine Learning 39(2/3), 135–168 (2000)
Tsinaraki, C., Polydoros, K.F., Christodoulakis, S.: Ontology-based semantic indexing for mpeg-7 and tv-anytime audiovisual content. Multimedia Tools and Applications 26(3), 299–325 (2005)
Uschold, M., King, M.: Towards a Methodology for Building Ontologies. In: Proceedings of the Workshop on Basic Ontological Issues in Knowledge Sharing, Held in Conduction with IJCAI 1995, pp. 6.1–6.10 (1995)
Wanner, L., Bohnet, B., Bouayad-Agha, N., Lareau, F., Nicklass, D.: MARQUIS: Generation of User-Tailored Multilingual Air Quality Bulletins. Applied Artificial Intelligence 24(10), 914–952 (2010)
Wilcock, G.: Talking owls: Towards an ontology verbalizer. In: Proceedings of the Human Language Technology for the Semantic Web and Web Services, ISWC 2003, Sanibel Island, Florida, pp. 109–112 (2003)
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Bouayad-Agha, N., Casamayor, G., Wanner, L., Díez, F., López Hernández, S. (2011). FootbOWL: Using a Generic Ontology of Football Competition for Planning Match Summaries. In: Antoniou, G., et al. The Semantic Web: Research and Applications. ESWC 2011. Lecture Notes in Computer Science, vol 6643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21034-1_16
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DOI: https://doi.org/10.1007/978-3-642-21034-1_16
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