Inference of Absolute Time Value from Temporal Expressions
Inference of Absolute Time Value from Temporal Expressions
复制标题
从时间表达式推断绝对时间值
DOI：
10.1109/bigdata52589.2021.9671863
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Sekino Tatsuki
中科院分区：
文献类型：
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作者：
Sung Junehwan;Mori Shinsuke;Kameko Hirotaka;Kubo Akira;Sekino Tatsuki
在本文中，我们探索和讨论了一种从自然语言文本中提取时间信息的方法。该方法分为时态表达式识别和时态值推理两部分。前者采用传统的NER方法，使用BiLSTM-CRF架构。后者是用基于规则的算法实现的，该算法可以在以后的工作中进一步开发，以更好地覆盖各种时间表达式。在语料库方面，我们从一家主要的日本报纸公司中选择了200篇文章来创建一个带注释的语料库，将时态表达分为五种不同的类型。在性能方面，对于时间表达式的识别，我们的F-measure达到了0.866，对于表达式的绝对时间值的推断，我们的准确率达到了0.920。结合两个模块作为端到端系统运行，F-measure达到0.891。
In this paper, we explore and discuss a way to extract temporal information from natural language texts. The suggested method is divided into two parts: temporal expression recognition and temporal value inference. The former employs the conventional NER approach, using a BiLSTM-CRF architecture. The latter is implemented with a rule-based algorithm, which can be further developed in later work for better coverage of various temporal expressions. In terms of the corpus, we have selected 200 articles from one of the major Japanese newspaper companies to create an annotated corpus, classifying temporal expressions into five different types. As for the performance, we have achieved 0.866 in F-measure for the recognition of temporal expressions and 0.920 in accuracy for the inference of the absolute temporal values of the expressions. Combining the two modules and running them as an end-to-end system, we have attained 0.891 of F-measure.