1 research outputs found
Event Coreference Resolution Using Neural Network Classifiers
This paper presents a neural network classifier approach to detecting both
within- and cross- document event coreference effectively using only event
mention based features. Our approach does not (yet) rely on any event argument
features such as semantic roles or spatiotemporal arguments. Experimental
results on the ECB+ dataset show that our approach produces F1 scores that
significantly outperform the state-of-the-art methods for both within-document
and cross-document event coreference resolution when we use B3 and CEAFe
evaluation measures, but gets worse F1 score with the MUC measure. However,
when we use the CoNLL measure, which is the average of these three scores, our
approach has slightly better F1 for within- document event coreference
resolution but is significantly better for cross-document event coreference
resolution