一个包含108个具有主动和被动释义的新颖名词-名词复合词的数据集。
A Dataset of 108 Novel Noun-Noun Compound Words with Active and Passive Interpretation.
作者信息
Chen Phoebe, Poeppel David, Zuanazzi Arianna
机构信息
Department of Psychology, New York University, New York, NY, USA.
Center for Language, Music and Emotion (CLaME), New York University, New York, NY, USA.
出版信息
J Open Psychol Data. 2023 Aug 29;11:14. doi: 10.5334/jopd.93. eCollection 2023.
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.
我们通过将具有较高和较低施事性（即在句子中作为施事的概率）的名词组合在一起，创建了一个包含205个英语小说名词-名词复合词（NNC，例如“doctor charity”）的数据集。我们从58名以英语为母语的人群中收集了NNC的主动和被动解释。然后，我们使用从68名以英语为母语的人群中获得的数据，测量了具有主动和被动解释的NNC之间的解释时间差异（即108个NNC）。数据是通过众包平台（SONA和Prolific）在线收集的。数据集可在osf.io/gvc2w/上获取，可用于解决有关语义和句法构成的问题。
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