In this sense, our study also contributes to the study of words that exhibit part-of-speech ambiguities. Our analysis of particles provides a detailed account of various sub-uses that correspond to different parts of speech, their relationships, and relative distribution. We show that our enriched scheme makes it possible for a part-of-speech tagger to achieve more useful results. We offer an alternative tagging scheme that eliminates the category of ʻparticleʼ altogether. We show that the current tagging of particles in the manually disambiguated Morphological Standard of the Russian National Corpus is not entirely consistent, and that this can create challenges for training a part-of-speech tagger. We focus on nine high-frequency words commonly classed as particles: ešče, tak, ved’, slovno, daže, že, li, da, net. Our corpus analysis of Russian particles addresses theoretical questions about the cognitive status of parts of speech and practical concerns about how particles should be represented in computational models. Russian particles lack a coherent conceptual basis as a category and many are ambiguous with respect to part of speech. We propose a reclassification of Russian particles that implements Zwicky’s directive.

In 1985, Zwicky argued that ʻparticleʼ is a pretheoretical notion that should be eliminated from linguistic analysis.

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