Paper: A Sequencing Model for Situation Entity Classification

ACL ID P07-1113
Title A Sequencing Model for Situation Entity Classification
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

Situation entities (SEs) are the events, states, generic statements, and embedded facts and propositions introduced to a discourse by clauses of text. We report on the first data- driven models for labeling clauses according to the type of SE they introduce. SE classifi- cation is important for discourse mode iden- tification and for tracking the temporal pro- gression of a discourse. We show that (a) linguistically-motivated cooccurrence fea- tures and grammatical relation information from deep syntactic analysis improve clas- sification accuracy and (b) using a sequenc- ing model provides improvements over as- signing labels based on the utterance alone. We report on genre effects which support the analysis of discourse modes having charac- teristic distributions and sequences of SEs.