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DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers

机译:DeepCx:一种基于过渡的方法,用于使用复杂构造触发器进行浅层语义解析

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This paper introduces the surface construction labeling (SCL) task, which expands the coverage of Shallow Semantic Parsing (SSP) to include frames triggered by complex constructions. We present DeepCx, a neural, transition-based system for SCL. As a test case for the approach, we apply DeepCx to the task of tagging causal language in English, which relies on a wider variety of constructions than are typically addressed in SSP. We report substantial improvements over previous tagging efforts on a causal language dataset. We also propose ways DeepCx could be extended to still more difficult constructions and to other semantic domains once appropriate datasets become available.
机译:本文介绍了表面构造标注(SCL)任务,该任务扩展了“浅层语义分析(SSP)”的覆盖范围,以包括由复杂构造触发的框架。我们介绍了DeepCx,这是一种用于SCL的基于神经的,基于过渡的系统。作为该方法的测试用例,我们将DeepCx应用于用英语标记因果语言的任务,该因果关系依赖于比SSP中通常处理的结构更广泛的结构。我们报告了因果语言数据集上的先前标记工作的重大改进。我们还提出了在适当的数据集可用后,可以将DeepCx扩展到更困难的构造以及其他语义域的方法。

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