Identifying Expressions of Opinion in Context
Identifying Expressions of Opinion in Context
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发表时间：
2007-01
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通讯作者：
Eric Breck;Yejin Choi;Claire Cardie
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作者：
Eric Breck;Yejin Choi;Claire Cardie
虽然传统的信息提取系统是为了回答有关事实的问题，但主观信息提取系统将回答有关感受和观点的问题。实现这一目标的关键一步是识别文本中表达观点的单词和短语。事实上，尽管之前的许多工作都依赖于各种基于情感的 NLP 任务的意见表达识别，但没有一个直接关注这一重要的支持任务。此外，所提出的用于识别意见表达的方法都没有在其设计执行的任务中进行评估。我们提出了一种使用条件随机字段来识别意见表达的方法，并使用标准情感语料库在表达级别评估该方法。我们的方法实现了表达水平性能与人类注释者一致性的 5% 以内。
While traditional information extraction systems have been built to answer questions about facts, subjective information extraction systems will answer questions about feelings and opinions. A crucial step towards this goal is identifying the words and phrases that express opinions in text. Indeed, although much previous work has relied on the identification of opinion expressions for a variety of sentiment-based NLP tasks, none has focused directly on this important supporting task. Moreover, none of the proposed methods for identification of opinion expressions has been evaluated at the task that they were designed to perform. We present an approach for identifying opinion expressions that uses conditional random fields and we evaluate the approach at the expression-level using a standard sentiment corpus. Our approach achieves expression-level performance within 5% of the human interannotator agreement.