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Using Electronic Dictionaries and NooJ to Generate Sentences Containing English Phrasal Verbs

机译:使用电子词典和NooJ生成包含英语短语动词的句子

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This paper attempts to explore NooJ's "generation" mode to automatically produce transformations of sentences containing English Phrasal Verbs (PV). We exploit the same electronic dictionary and grammar previously used to recognize PV in large corpora (Machonis 2010, 2012), but have had to design a specific grammar for generating sentences, following the examples in Silberztein (2016), which showed how NooJ could generate over two million transformations or parallel sentences from the simple sentence Joe likes Lea. We created a grammar that can generate variations of a single phrase containing one of the PV found in the NooJ PV dictionary. For the moment the grammar only handles singular nouns in the present and past tense, but it is capable of applying a succession of transformations - particle movement, preterit, negation, clefting, modal insertion, aspect introduction, question formation, and passive voice, along with various combinations of these transformations - to over 1,200 PV from the electronic dictionary.
机译:本文试图探索NooJ的“生成”模式,以自动产生包含英语短语动词(PV)的句子的转换。我们利用了以前用于识别大型语料库中的PV的相同电子词典和语法(Machonis,2010年,2012年),但必须根据Silberztein(2016年)中的示例设计一种特定的语法来生成句子,该示例展示了NooJ如何生成乔喜欢Lea的简单句子中有超过200万个转换或平行句子。我们创建了一个语法,可以生成包含在NooJ PV词典中找到的PV的单个短语的变体。目前,语法仅处理当前时态和过去时态中的单数名词,但能够应用一系列转换-粒子运动,惯用语言,否定,开裂,模态插入,方面介绍,问题形成和被动语态,以及这些转换的各种组合-从电子词典中获得超过1,200 PV。

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