Learning Event Semantics From Online News
In this paper we present a multilingual algorithm for automatic extension of an event extraction grammar by unsupervised learning of semantic clusters of terms. In particular, we tested our algorithm to learn terms which are relevant for detection of displacement and evacuation events. Such events constitute an important part in the process of development of humanitarian crises, confliicts and natural and man made disasters. Apart from the grammar extension we consider our learning algorithm and the obtained semantic classes as a first step towards the semi-automatic building of a domain-specic ontology of disaster events. We carried out experiments both for English and Spanish languages and obtained promising results.
TANEV Hristo;
KABADJOV Mijail;
GEMO Monica;
2010-03-24
BAHRI Publications
JRC57552
0976-0962,
https://publications.jrc.ec.europa.eu/repository/handle/JRC57552,
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