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Modeling the frequency of phrasal verbs with search engines

机译:使用搜索引擎建模短语动词的频率

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There are well over a thousand phrasal verbs in English. For non-native speakers they are notoriously difficult to remember and use in the right context. We tried to construct a ranking of phrasal verbs according to their estimated occurrence frequency, based on quantitative information available from the public indexable Web. Technically, we used major Web search engines to acquire phrase-occurrence statistics, measured consistency between the rankings implied by their results and confirmed that a rough set of ‘classes’ of phrasal verbs can be distinguished. While this technique relies on inaccurate and possibly biased estimation functions, we show that the overall distribution of ranks seems to be consistent among all the queried search engines operated by different vendors.
机译:在英语中有一千个短语动词。对于非母语人士,他们难以记住并在正确的背景下使用。根据可从公共可索引网络可获得的定量信息,我们试图根据其估计的发生频率来构建短语动词的排名。从技术上讲,我们使用了主要的网络搜索引擎来获取短语发生统计信息,所暗示的排名之间的测量一致性并确认可以区分短语动词的粗略的“类别”。虽然这种技术依赖于不准确和可能有偏见的估计函数,但我们表明,等级的整体分布似乎是由不同供应商运营的所有查询搜索引擎之间的一致。

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