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Supervised Machine Learning Techniques to Detect TimeML Events in French and English
Abstract : Identifying events from texts is an information extraction task necessary for many NLP applications. Through the TimeML specifications and TempEval challenges, it has received some attention in the last years; yet, no reference result is available for French. In this paper, we try to fill this gap by proposing several event extraction systems, combining for instance Conditional Random Fields, language modeling and k-nearest-neighbors. These systems are evaluated on French corpora and compared with state-of-the-art methods on English. The very good results obtained on both languages validate our whole approach.
Cited literature [25 references]
https://hal.archives-ouvertes.fr/hal-01226541
Contributor : Vincent Claveau Connect in order to contact the contributor
Submitted on : Monday, November 9, 2015 - 5:47:19 PM
Last modification on : Tuesday, March 15, 2022 - 3:22:21 AM
Long-term archiving on: : Wednesday, February 10, 2016 - 10:50:26 AM
Contributor : Vincent Claveau Connect in order to contact the contributor
Submitted on : Monday, November 9, 2015 - 5:47:19 PM
Last modification on : Tuesday, March 15, 2022 - 3:22:21 AM
Long-term archiving on: : Wednesday, February 10, 2016 - 10:50:26 AM
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NLDB_event.pdf
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