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- W2375333135 abstract "The semantic role labeling(SRL) is a new research area of natural language processing in recent years.Compared to the study in English,Chinese SRL is still in its infancy stage.In this paper,we focus on the semantic role classification(SRC),one key step of SRL.Besides introducing some new features,we also explore the inter-dependence of the semantic roles.We employ the context features to improve the performance of the semantic role classification.And a greedy algorithm is designed to select the different windows of the context for different feature templates,since the highest performance can be achieved with different window sizes for different feature templates.In the experiments,the precision of our SRC system can achieve 95.00%,proving the validness of our approach." @default.
- W2375333135 created "2016-06-24" @default.
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- W2375333135 date "2008-01-01" @default.
- W2375333135 modified "2023-09-26" @default.
- W2375333135 title "Maximum Entropy-Based Semantic Role Classification" @default.
- W2375333135 hasPublicationYear "2008" @default.
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