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Wikipedia-based WSD for multilingual frame annotation

机译:基于Wikipedia的WSD用于多语言框架注释

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摘要

Many applications in the context of natural language processing have been proven to achieve a significant performance when exploiting semantic information extracted from high-quality annotated resources. However, the practical use of such resources is often biased by their limited coverage. Furthermore, they are generally available only for English and few other languages. We propose a novel methodology that, starting from the mapping between FrameNet lexical units and Wikipedia pages, automatically leverages from Wikipedia new lexical units and example sentences. The goal is to build a reference data set for the semi-automatic development of new FrameNets. In addition, this methodology can be adapted to perform frame identification in any language available in Wikipedia. Our approach relies on a state-of-the-art word sense disambiguation system that is first trained on English Wikipedia to assign a page to the lexical units in a frame. Then, this mapping is further exploited to perform frame identification in English or in any other language available in Wikipedia. Our approach shows a high potential in multilingual settings, because it can be applied to languages for which other lexical resources such as WordNet or thesauri are not available.
机译:已经证明,在利用自然语言处理的上下文中的许多应用程序在利用从高质量带注释的资源中提取的语义信息时,可以实现显着的性能。但是,此类资源的实际使用通常会因其覆盖范围有限而产生偏差。此外,它们通常仅适用于英语和其他几种语言。我们提出了一种新颖的方法,该方法从FrameNet词法单位与Wikipedia页面之间的映射开始,自动利用Wikipedia中的新词法单位和例句。目的是为新的FrameNets的半自动开发建立参考数据集。另外,该方法可以适于以维基百科中可用的任何语言执行帧识别。我们的方法依赖于最先进的词义消歧系统,该系统首先在英语Wikipedia上进行训练,以将页面分配给框架中的词汇单元。然后,进一步利用此映射以英语或维基百科中可用的任何其他语言执行帧识别。我们的方法在多语言环境中显示出很高的潜力,因为它可以应用于其他词汇资源(例如WordNet或thesauri)不可用的语言。

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