Semantic Role Labeling is a shallow semantic parsing method.
语义角色标注是一种浅层语义分析的方法。
Semantic role labeling is a feasible proposal to shallow semantic parsing.
语义角色标注是浅层语义分析的一种可行方案。
In recent years, natural language processing is focusing on the semantic role labeling.
近年来，自然语言研究的热点已经转到了语义角色标注上来。
In particular, given a sentence and a predicate, semantic role labeling (SRL) identifies its semantic arguments and classifies their semantic roles.
作为其具体实现，语义角色标注的任务是识别并标注句中每个目标谓词的所有充当语义角色的句法成分。
Secondly, this paper proposed a method combined rule-based pos selection model with Statistics-based Cascading Conditional random field to conduct semantic Role Labeling of Chinese Question.
其次，本文选用了一种将基于统计方法的条件随机场模型与基于规则方法的词性筛选模型相结合的方式对中文问句进行语义角色自动标注。
Finally, Effective features of semantic Role Labeling of Questions were analyzed according to the experimental results, and the difference between question and declarative sentence was discussed.
最后，通过实验结果分析了问句语义角色标注的有效特征，对比了问句与陈述句标注的不同之处。
This is a satisfactory outcome in the Chinese semantic role labeling area, we believe that if more distinguishing features can be able to be joined, experimental results will be further enhanced.
这在中文语义角色标注领域是令人满意的结果，我们相信，如果后期能加入更具有区分性的特征，实验结果一定会进一步得到提高。
This is a satisfactory outcome in the Chinese semantic role labeling area, we believe that if more distinguishing features can be able to be joined, experimental results will be further enhanced.
这在中文语义角色标注领域是令人满意的结果，我们相信，如果后期能加入更具有区分性的特征，实验结果一定会进一步得到提高。
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