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- W4112856 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." @default.
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- W4112856 date "2012-09-27" @default.
- W4112856 modified "2023-09-27" @default.
- W4112856 title "KYOTO: A Knowledge-Rich Approach to the Interoperable Mining of Events from Text" @default.
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- W4112856 doi "https://doi.org/10.1007/978-3-642-31782-8_5" @default.
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