Annotation and Analysis of Extractive Summaries for the Kyutech Corpus
Annotation and Analysis of Extractive Summaries for the Kyutech Corpus
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发表时间：
2018-05
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通讯作者：
Takashi Yamamura;Kazutaka Shimada
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作者：
Takashi Yamamura;Kazutaka Shimada
多方对话的摘要是自然语言处理的重要任务之一。对于对话摘要任务，语料库在分析对话特征和构建摘要生成方法方面发挥着重要作用。我们正在开发一个免费的日语对话语料库，用于决策任务。我们称之为 Kyutech 语料库。 Kyutech 语料库的当前版本包含每个话语的主题标签和每个对话的参考摘要。在本文中，我们解释了提取摘要的注释任务。在注释任务中，我们为每个话语注释一个重要性标签，并将话语与 Kyutech 语料库中已有的参考摘要中的句子链接起来。通过使用带注释的提取摘要，我们可以在 Kyutech 语料库上评估提取摘要方法。在实验中，我们比较了一些基于机器学习技术的方法和一些特征。
Summarization of multi-party conversation is one of the important tasks in natural language processing. For conversation summarization tasks, corpora have an important role to analyze characteristics of conversations and to construct a method for summary generation. We are developing a freely available Japanese conversation corpus for a decision-making task. We call it the Kyutech corpus. The current version of the Kyutech corpus contains topic tags of each utterance and reference summaries of each conversation. In this paper, we explain an annotation task of extractive summaries. In the annotation task, we annotate an importance tag for each utterance and link utterances with sentences in reference summaries that already exist in the Kyutech corpus. By using the annotated extractive summaries, we can evaluate extractive summarization methods on the Kyutech corpus. In the experiment, we compare some methods based on machine learning techniques with some features.