Paper: Predicting Discourse Connectives for Implicit Discourse Relation Recognition

ACL ID C10-2172
Title Predicting Discourse Connectives for Implicit Discourse Relation Recognition
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

Existing works indicate that the absence of explicit discourse connectives makes it difficult to recognize implicit discourse relations. In this paper we attempt to overcome this difficulty for implicit rela- tion recognition by automatically insert- ing discourse connectives between argu- ments with the use of a language model. Then we propose two algorithms to lever- age the information of these predicted connectives. One is to use these pre- dicted implicit connectives as additional features in a supervised model. The other is to perform implicit relation recognition based only on these predicted connectives. Results on Penn Discourse Treebank 2.0 show that predicted discourse connectives help implicit relation recognition and the first algorithm can achieve an absolute av- erage f-scor...