Departmental Papers (CIS)

Date of this Version

8-2009

Document Type

Conference Paper

Comments

Pitler, E., Louis, A., & Nenkova, A., Automatic Sense Prediction for Implicit Discourse Relations in Text, 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Aug. 2009, doi: anthology/P09-1077

Abstract

We present a series of experiments on automatically identifying the sense of implicit discourse relations, i.e. relations that are not marked with a discourse connective such as “but” or “because”. We work with a corpus of implicit relations present in newspaper text and report results on a test set that is representative of the naturally occurring distribution of senses. We use several linguistically informed 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 features, explain some of their shortcomings and propose modifications. Our best combination of features outperforms the baseline from data intensive approaches by 4% for comparison and 16% for contingency.

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Date Posted: 30 July 2012