Automatic Extraction of Negative Polarity Items

Student: Bibaeva Mariya

Supervisor: Francis M. Tyers

Educational Programme: Fundamental and Computational Linguistics (Bachelor)

Year of Graduation: 2018

Negative and positive polarity items are a well-explored topics in formal semantics and typology. However, the phenomenon is mostly addressed to a very limited linguistic material, such as indefinite pronouns, idioms or adverbs, since polarity items are rather rare and often hard to spot. The goal of this work was to expand the list of known polarity items in Russian language and at the same time provide a computational tool which could be used in further research. The approach is based on applying the knowledge of licensing contexts that allow to use NPIs and PPIs, respectively, to corpus data and revealing fuller set of polarized items in natural languages by use of computational and statistical methods of analysis.

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