Paper: Cascading Collective Classification for Bridging Anaphora Recognition using a Rich Linguistic Feature Set

ACL ID D13-1077
Title Cascading Collective Classification for Bridging Anaphora Recognition using a Rich Linguistic Feature Set
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Recognizing bridging anaphora is difficult due to the wide variation within the phenomenon, the resulting lack of easily identifiable surface markers and their relative rarity. We develop linguistically motivated discourse structure, lexico-semantic and genericity detection fea- tures and integrate these into a cascaded mi- nority preference algorithm that models bridg- ing recognition as a subtask of learning fine- grained information status (IS). We substan- tially improve bridging recognition without impairing performance on other IS classes.