NLP-Driven Event Semantic Ontology Modeling for Story
This paper presents a NLP-driven semantic ontology modeling for unstructured data of Chinese children stories. We use a weakly-supervised approach to capture n-ary facts based on the output of dependency parser and regular expressions. After n-ary facts post-processing, we populate the extracted facts of events to SOSDL (Story-Oriented Semantic Language), an event ontology designed for modeling semantic elements and relations of events, to form a machine-readable format. Experiments indicate the reasonability and feasibility of our approach.
KeywordsInformation Extraction Natural Language Processing N-ary Relation Event Ontology
Unable to display preview. Download preview PDF.
- 1.Wang, W.: Chinese News Event 5WH Semantic Elements Extraction for Event Ontology Population. In: Proceedings of the 21st International Conference Companion on World Wide Web, Lyon, France, pp. 197–202 (2012)Google Scholar
- 2.Liu, Y.H.: Chinese Event Extraction Based on Syntactic Analysis. MA Thesis. Shang Hai University, China (2009)Google Scholar
- 3.Gamallo, P., Garcia, M.: Dependency-Based Open Information Extraction. In: Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, Avignon, France, pp. 10–18 (2012)Google Scholar
- 5.Chang, P.C., Tseng, H., Jurafsky, D., Manning, C.D.: Discriminative Reordering with Chinese Grammatical Relations Features (2010), http://nlp.stanford.edu/pubs/ssst09-chang.pdf
- 6.Ruiz de Mendoza Ibáñez, F.J., Mairal Usón, R.: Levels of description and constraining factors in meaning construction: an introduction to the Lexical Constructional Model (2008), http://www.lexicom.es/drupal/files/RM_Mairal_2008_Folia_Linguistica.pdf