A Maximum Entropy Classifier for Cross-Lingual Pronoun Prediction
Dominikus Wetzel, Adam Lopez, Bonnie Webber · 2015
We present a maximum entropy classifier for cross-lingual pronoun prediction.The features are based on local source-and target-side contexts and antecedent information obtained by a co-reference resolution system.With only a small set of feature types our best performing system achieves an accuracy of 72.31%.According to the shared task's official macroaveraged F1-score at 57.07%, we are among the top systems, at position three out of 14. Feature ablation results show the important role of target-side information in general and of the resolved targetside antecedent in particular for predicting the correct classes.