Abstract This paper presents token-based semantic vector spaces as a tool that can be applied in corpus-linguistic analyses such as word sense comparisons, comparisons of synonymous lexical items, and matching of concordance lines with a given text. We demonstrate how token-based semantic vector spaces are created, and we illustrate the kinds of result that can be obtained with this approach. Our main argument is that token-based semantic vector spaces are not only useful for practical corpus-linguistic applications but also for the investigation of theory-driven questions. We illustrate this point with a discussion of the asymmetric priming hypothesis (Jäger and Rosenbach 2008). The asymmetric priming hypothesis, which states that grammaticalizing constructions will be primed by their lexical sources but not vice versa, makes a number of empirically testable predictions. We operationalize and test these predictions, concluding that token-based semantic vector spaces yield conclusions that are relevant for linguistic theory-building.

中文翻译：

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使用基于令牌的语义向量空间进行语料库语言分析：从实际应用到理论主张的测试

摘要本文提出了基于令牌的语义向量空间作为一种工具，可将其用于诸如词义比较，同义词项目的比较以及一致行与给定文本的匹配等语料库语言分析中。我们演示了如何创建基于令牌的语义向量空间，并演示了使用这种方法可以获得的结果。我们的主要论点是，基于令牌的语义向量空间不仅对实际的语料库语言应用有用，而且对理论驱动的问题的研究也很有用。我们通过讨论非对称启动假设来说明这一点（Jäger和Rosenbach 2008）。非对称启动假说，该假说指出语法化构造将由其词汇来源启动，反之亦然，进行了大量的经验检验的预测。我们对这些预测进行了操作和测试，认为基于令牌的语义向量空间得出的结论与语言理论的建立有关。