Abstract
In this paper, we propose a method for creating automatically weighted lexicons of event names. Almost all names of events are ambiguous in context (i.e., they can be interpreted in an eventive or non-eventive reading). Therefore, weights representing the relative “eventiveness” of a noun can help for disambiguating event detection in texts.
We applied our method on both French and English corpora. Our method has been applied to both French and English corpora. We performed an evaluation based upon a machine-learning approach that shows that using weighted lexicons can be a good way to improve event extraction. We also propose a study concerning the necessary size of corpus to be used for creating a valuable lexicon.
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Arnulphy, B., Tannier, X., Vilnat, A. (2012). Automatically Generated Noun Lexicons for Event Extraction. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28601-8_19
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DOI: https://doi.org/10.1007/978-3-642-28601-8_19
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