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.
['Béatrice Arnulphy', 'Vincent Claveau', 'Xavier Tannier', 'Anne Vilnat']
Supervised Machine Learning Techniques to Detect TimeML Events in French and English