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In this paper, we attempt to link the inner workings of a neural languagemodel to linguistic theory, focusing on a complex phenomenon well discussed informal linguis- tics: (negative) polarity items. We briefly discuss the leadinghypotheses about the licensing contexts that allow negative polarity items andevaluate to what extent a neural language model has the ability to correctlyprocess a subset of such constructions. We show that the model finds a relationbetween the licensing context and the negative polarity item and appears to beaware of the scope of this context, which we extract from a parse tree of thesentence. With this research, we hope to pave the way for other studies linkingformal linguistics to deep learning.

Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items