A Dataset of 108 Novel Noun-Noun Compound Words with Active and Passive Interpretation

Phoebe Chen; David Poeppel; Arianna Zuanazzi

doi:10.5334/jopd.93

Abstract

We created a dataset of 205 English novel noun-noun compounds (NNCs, e.g., “doctor charity”) by combining nouns with higher and lower agentivity (i.e., the probability of being an agent in a sentence). We collected active and passive interpretations of NNCs from a group of 58 English native speakers. We then measured interpretation time differences between NNCs with active and passive interpretations (i.e., 108 NNCs), using data obtained from a group of 68 English native speakers. Data were collected online using crowdsourcing platforms (SONA and Prolific). The datasets are available at osf.io/gvc2w/ and can be used to address questions about semantic and syntactic composition.

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A Dataset of 108 Novel Noun-Noun Compound Words with Active and Passive Interpretation

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