Abstract
To automatically understand text, a crucial step is to extract events and their participants. The same event can be packaged in many different ways in a language. Capturing all these ways with sufficient precision is a major challenge. This becomes even more complex, when we consider texts in different languages on the same topic. We describe a knowledge-rich event-mining system developed for the Asian-European project KYOTO that can extract events in a uniform and interoperable way, regardless of the way they are expressed and in which language. To achieve this, we developed an open text representation format, semantic processing modules and a central ontology that is shared across seven languages. We implemented a semantic tagging approach that performs off-line reasoning and a module for detecting semantic and linguistic patterns in the tagged data to extract events from a large variety of expressions. The system can efficiently handle large volumes of documents and is not restricted to a specific domain. We applied the system to an English text on estuaries.
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Notes
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DOLCE-Lite-Plus version 3.9.7
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This knowledge model is freely available through the KYOTO website as open-source data.
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The mapping relations from wordnet to the ontology, need to satisfy the constraints of the ontology, i.e. only roles can be expressed that are compatible with the role-schema of the process in which they participate.
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For cross-lingual retrieval, the lemmas have been translated to all the other languages in KYOTO, using the equivalences in the wordnets. The databases can be searched in any of the languages and the results are rendered in the query languages, regardless of the source language of the information.
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Follow the next URL to search in the Estuary database. Login with any name and any password: http://kyoto.irion.nl/kyoto/web/init.do?project=estuary_en&database=2&queryLg=en&query=
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Acknowledgements
The KYOTO project is co-funded by EU –FP7 ICT Work Programme 2007 under Challenge 4 –Digital libraries and Content, Objective ICT-2007.4.2 (ICT-2007.4.4): Intelligent Content and Semantics (challenge 4.2). The Asian partners from Tapei and Kyoto are funded from national funds. This work has been also supported by Spanish project KNOW-2 (TIN2009-14715-C04-01).
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Vossen, P., Agirre, E., Rigau, G., Soroa, A. (2013). KYOTO: A Knowledge-Rich Approach to the Interoperable Mining of Events from Text. In: Oltramari, A., Vossen, P., Qin, L., Hovy, E. (eds) New Trends of Research in Ontologies and Lexical Resources. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31782-8_5
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