A 5W1H Based Annotation Scheme for Semantic Role Labeling of English Tweets
A 5W1H Based Annotation Scheme for Semantic Role Labeling of English Tweets
复制标题
基于5W1H的英文推文语义角色标注标注方案
DOI：
10.13053/cys-22-3-3016
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Amitava Das
中科院分区：
文献类型：
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作者：
Kunal Chakma;Amitava Das
语义角色标签（SRL）是自然语言处理的一个深入研究的领域。 SRL 已针对正式文本开发了最先进的词汇资源，这些资源涉及繁琐的注释方案并需要语言专业知识。当这种复杂的注释方案应用于推文以识别谓词和角色参数时，困难会增加很多。在本文中，我们提出了一种用于英语推文注释的简化方法，用于识别谓词和相应的语义角色。为了注释目的，我们采用了新闻业广泛使用的 5W1H（Who、What、When、Where、Why 和 How）概念。 5W1H 任务旨在通过将自然语言句子中的语义信息提炼为 5W1H 问题的答案来提取语义信息：谁、什么、何时、何地、为什么和如何。 5W1H 方法对于 ProbBank 语义角色标记任务来说相对简单方便。我们报告了我们的 SRL 注释方案在推文上的性能，并表明非专家注释者可以为推文生成高质量的 SRL 数据。本文还报告了 Twitter 数据语义角色标记所涉及的困难和挑战，并提出了解决方案。
Semantic Role Labeling (SRL) is a well researched area of Natural Language Processing. State-of-the-art lexical resources have been developed for SRL on formal texts that involve a tedious annotation scheme and require linguistic expertise. The difficulties increase manifold when such complex annotation scheme is applied on tweets for identifying predicates and role arguments. In this paper, we present asimplified approach for annotation of English tweets for identification of predicates and corresponding semantic roles. For annotation purpose, we adopted the 5W1H (Who, What, When, Where, Why and How) concept which is widely used in journalism. The 5W1H task seeks to extract the semantic information in a natural language sentence by distilling it into the answers to the 5W1H questions: Who, What, When, Where, Why and How. The 5W1H approach is comparatively simple and convenient with respect to the ProbBank Semantic Role Labeling task. We report an the performance of our annotation scheme for SRL on tweets and show that non-expert annotators can produce quality SRL datafor tweets. This paper also reports the difficulties and challenges involved with semantic role labeling on twitter data and propose solutions to them.