A two-phase external-knowledge plus number-learning-network method for multi-label charge prediction yields 3-5% macro-F1 and 5-15% micro-F1 gains when added to existing deep models on a Chinese legal dataset.
In: EMNLP 2014, October 25-29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL
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An External Knowledge Enhanced Multi-label Charge Prediction Approach with Label Number Learning
A two-phase external-knowledge plus number-learning-network method for multi-label charge prediction yields 3-5% macro-F1 and 5-15% micro-F1 gains when added to existing deep models on a Chinese legal dataset.