Paper: Aligning Predicates across Monolingual Comparable Texts using Graph-based Clustering

ACL ID D12-1016
Title Aligning Predicates across Monolingual Comparable Texts using Graph-based Clustering
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

Generating coherent discourse is an important aspect in natural language generation. Our aim is to learn factors that constitute coherent discourse from data, with a focus on how to re- alize predicate-argument structures in a model that exceeds the sentence level. We present an important subtask for this overall goal, in which we align predicates across compara- ble texts, admitting partial argument struc- ture correspondence. The contribution of this work is two-fold: We first construct a large corpus resource of comparable texts, includ- ing an evaluation set with manual predicate alignments. Secondly, we present a novel ap- proach for aligning predicates across compa- rable texts using graph-based clustering with Mincuts. Our method significantly outper- forms other alignment technique...