|Date of Submission||June 23, 2020, 4:40 p.m.|
|Resource Type||Primary Text|
|Access Medium||Web Download|
SemTransCNC was developed by The Hong Kong Polytechnic University. It is comprised of a semantic transparency dataset of Chinese nominal compounds built using a series of crowd-based experiments.
Nominal compounds were selected from the Sinica Corpus and a modern Chinese lexicon. Crowd workers answered questionnaires that included demographic information and questions about the Chinese language. For assessing overall semantic transparency (OST) of selected compounds, they answered the question: "How is the sum of the meanings of A and B similar to the meaning of AB?" For assessing constituent semantic transparency (CST), they were asked to describe the similarity of A alone to its meaning in AB and the meaning of B alone to its meaning in AB.
SemTransCNC consists of OST and CST data for 1,176 dimorphemic Chinese nominal compounds, which consist of free morphemes and have mid-range frequencies.
The text data is presented as a UTF-8 encoded comma separated text file.
|Creator||Chu-Ren Huang , Shichang Wang , Yao Yao , Angel Chan|
|Distributor||Linguistic Data Consortium|
|Rights Holder||Portions © 2020 The Hong Kong Polytechnic University, © 2020 Trustees of the University of Pennsylvania|