Abstract
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.
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Gao, CM., Xie, QM., Wang, XL. (2013). NLP-Driven Event Semantic Ontology Modeling for Story. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2013. Lecture Notes in Computer Science, vol 7934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38824-8_41
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DOI: https://doi.org/10.1007/978-3-642-38824-8_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38823-1
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