文本叙事结构分析中的事件自动提取方法

Hye-Yeon Yu, Moonhyun Kim
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引用次数: 1

摘要

本文分析了当代从文本叙事中提取事件的方法和各种事件表达格式。本文还简要讨论了人工智能在叙事理解和生成方面的未来发展方向。分析了从文本故事中提取事件的三步学习方法,包括标记分析和词性标记、依赖解析和标准化工作。使用元组格式创建的表达式将与使用5W格式创建的表达式进行比较和对比。最后,我们提出了一种以元组格式组织事件的新方法,将复合句和复杂句重构为简单句。我们的方法识别和提取动词、主语、宾语和介词短语。然后,它会自动提取组成每个句子的多个事件。
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Automatic Event Extraction method for Analyzing Text Narrative Structure
This paper presents an analysis of contemporary methods for event extraction from text narratives and of various event expression formats. It also briefly discusses future directions in narrative understanding and generation using artificial intelligence. The three-step study method for extracting events from text stories, comprising token analysis and part-of-speech tagging, dependent parsing, and standardization work, is analyzed. Expressions created using a tuple format are compared and contrasted with expressions created using the 5W format. Finally, we propose a novel method to organize events in a tuple format, reconstructing compound and complex sentences as simple sentences. Our method identifies and extracts verbs, subject, object, and preposition phrases. It then automatically extracts the multiple events that comprise each sentence.
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