A Maximum Entropy Classifier for Cross-Lingual Pronoun Prediction
نویسندگان
چکیده
We present a maximum entropy classifier for cross-lingual pronoun prediction. The features are based on local sourceand 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.
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