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Combining Natural and Artificial Examples to Improve Implicit Discourse Relation Identification
International Conference on Computational Linguistics
This paper presents the first experiments on identifying implicit discourse relations (i.e., relations lacking an overt discourse connective) in French. Given the little amount of annotated data for this task, our system resorts to additional data automatically labeled using unambiguous connectives, a method introduced by (Marcu and Echihabi, 2002) . We first show that a system trained solely on these artificial data does not generalize well to natural implicit examples, thus echoing thedblp:conf/coling/BraudD14 fatcat:cjoqjdmpare3nlrc7g7lvlriaa