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Crowdsourcing-Based Evaluation of Automatic References Between WordNet and Wikipedia

机译:基于众包的WordNet与Wikipedia之间自动引用的评估

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The paper presents an approach to build references (also called mappings) between WordNet and Wikipedia. We propose four algorithms used for automatic construction of the references. Then, based on an aggregation algorithm, we produce an initial set of mappings that has been evaluated in a cooperative way. For that purpose, we implement a system for the distribution of evaluation tasks, that have been solved by the user community. To make the tasks more attractive, we embed them into a game. Results show the initial mappings have good quality, and they have also been improved by the community. As a result, we deliver a high quality dataset of the mappings between two lexical repositories: WordNet and Wikipedia, that can be used in a wide range of NLP tasks. We also show that the framework for collaborative validation can be used in other tasks that require human judgments.
机译:本文提出了一种在WordNet和Wikipedia之间建立引用(也称为映射)的方法。我们提出了四种用于自动构建参考的算法。然后,基于聚合算法,我们生成了一组以协作方式评估的初始映射。为此,我们实施了一个用于分配评估任务的系统,该系统已由用户社区解决。为了使任务更具吸引力,我们将它们嵌入了游戏中。结果表明,初始映射具有良好的质量,并且社区也对其进行了改进。结果,我们提供了两个词汇库之间的映射的高质量数据集:WordNet和Wikipedia,可用于各种NLP任务。我们还表明,用于协作验证的框架可用于需要人工判断的其他任务。

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