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Recognition of Person Relation Indicated by Predicates

机译:谓词所表示的人际关系的认可

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This paper focuses on recognizing person relations indicated by predicates from large scale of free texts. In order to determine whether a sentence contains a potential relation between persons, we cast this problem to a classification task. Dynamic Convolution Neural Network (DCNN) is improved for this task. It uses frame convolution for making uses of more features efficiently. Experimental results on Chinese person relation recognition show that the proposed model is superior when compared to the original DCNN and several strong baseline models. We also explore employing large scale unlabeled data to achieve further improvements.
机译:本文着重于从大量自由文本中识别谓词所指示的人际关系。为了确定句子是否包含人与人之间的潜在关系,我们将此问题归类为分类任务。动态卷积神经网络(DCNN)为此任务进行了改进。它使用帧卷积来有效利用更多功能。中国人际关系识别的实验结果表明,与原始DCNN和几种强基线模型相比,该模型具有优越性。我们还探索了使用大规模未标记数据来实现进一步的改进。

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