How nouns surface as verbs: Inference and generation in word class conversion

AbstractWord class conversion refers to the extended use of a word from one grammatical class to another without overt morphological marking. Noun-to-verb conversion, or denominalization, is one form of word class conversion studied extensively in the literature. Previous work has suggested that novel denominal verb usages are comprehensible if the listener can compute the intended meaning based on shared knowledge with the speaker. However, no existing work has explored the computational mechanism under this proposal. We propose a frame-semantic generative model, Noun2Verb, that supports the inference and generation of novel denominal verb usages via semi-supervised learning. We evaluate this framework in a dataset of denominal verbs drawn from adults and children against a state-of-the-art model from natural language processing. Our results show that Noun2Verb aligns better with human interpretation and bridges the gap between machines and humans in lexical innovation.

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