Cascading Collective Classification for Bridging Anaphora Recognition using a Rich Linguistic Feature Set
Yufang Hou, Katja Markert, Michael Strube · 2013
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 features and integrate these into a cascaded minority preference algorithm that models bridging recognition as a subtask of learning finegrained information status (IS).We substantially improve bridging recognition without impairing performance on other IS classes.