Improving Chinese Semantic Role Labeling with English Proposition Bank
نویسندگان
چکیده
Most researches to SRL focus on English. It is still a challenge to improve the SRL performance of other language. In this paper, we introduce a twopass approach to do Chinese SRL with a Recurrent Neural Network (RNN) model. We use English Proposition Bank (EPB) to improve the performance of Chinese SRL. Experimental result shows a significant improvement over the stateof-the-art methods on Chinese Proposition Bank (CPB), which reaches 78.39% F1 score.
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