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Subject Recognition in Chinese Sentences for Chatbots

机译:聊天机器人中文句子中的主题识别

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摘要

Subject (In this paper, subject means '主体/zhu ti' in Chinese, while we use 'grammatical subject' to denote traditional '主语/zhu yu' in Chinese.) recognition plays a significant role in the conversation with a Chatbot. The misclassification of the subject of a sentence leads to the misjudgment of the intention recognition. In this paper, we build a new dataset for subject recognition and propose several systems based on pre-trained language models. We first design annotation guidelines for human-chatbot conversational data, and hire anno-tators to build a new dataset according to the guidelines. Then, classification methods based on deep neural network are proposed. Finally, extensive experiments are conducted to testify the performance of different algorithms. The results show that our method achieves 88.5% F_1 in the task of subject recognition. We also compare our systems with three other Chatbot systems and find ours perform the best.
机译:主题(在本文中,主题在中文中意为“主体/ zhu ti”,而在中文中,我们使用“语法主题”表示传统的“主语/ zhu yu”。)识别在与聊天机器人的对话中起着重要作用。句子主语的错误分类导致意图识别的错误判断。在本文中,我们建立了一个新的主题识别数据集,并提出了一些基于预训练语言模型的系统。我们首先为人类聊天机器人的对话数据设计注释准则,然后根据该准则雇用注释者来构建新的数据集。然后,提出了基于深度神经网络的分类方法。最后,进行了广泛的实验以证明不同算法的性能。结果表明,我们的方法在主题识别任务中达到了88.5%的F_1。我们还将我们的系统与其他三个Chatbot系统进行比较,发现我们的系统性能最佳。

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