Paper: Automatic sense prediction for implicit discourse relations in text

ACL ID P09-1077
Title Automatic sense prediction for implicit discourse relations in text
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

We present a series of experiments on au- tomatically identifying the sense of im- plicit discourse relations, i.e. relations that are not marked with a discourse con- nective such as “but” or “because”. We work with a corpus of implicit relations present in newspaper text and report re- sults on a test set that is representative of the naturally occurring distribution of senses. We use several linguistically in- formed features, including polarity tags, Levin verb classes, length of verb phrases, modality, context, and lexical features. In addition, we revisit past approaches using lexical pairs from unannotated text as fea- tures, explain some of their shortcomings and propose modifications. Our best com- bination of features outperforms the base- line from data intensive approac...