轮询博客圈:基于规则的信念分类方法

Jason S Kessler
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引用次数: 9

摘要

这里描述的研究是一个更大项目的一部分,目的是确定作者是否相信一个命题是真的或假的。这项任务需要对命题的语义上下文有深刻的理解,这远远超出了NLP的技术水平。鉴于这一困难,本文提出了一个浅语义框架,解决了在句子层面上寻找命题真值的子问题。该框架由几类语言元素组成,当这些语言元素通过特定的词典句法连接器与命题联系起来时,就会改变命题的真值。对实施该框架的系统的试点评估产生了有希望的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Polling the Blogosphere: A Rule-Based Approach to Belief Classification
The research described here is part of a larger project with the objective of determining if a writer believes a proposition to be true or false. This task requires a deep understanding of a proposition's semantic context, which is far beyond NLP's state of the art. In light of this difficulty, this paper presents a shallow semantic framework that addresses the sub-problem of finding a proposition's truth-value at the sentence level. The framework consists of several classes of linguistic elements that, when linked to a proposition through specific lexico-syntactic connectors, change its truth-value. A pilot evaluation of a system implementing this framework yields promising results.
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