|Author(s):||Shichang Wang, Chu-Ren Huang, Yao Yao, Angel Chan|
|LDC Catalog No.:||LDC2020T12|
|Release Date:||June 22, 2020|
|Data Source(s):||web collection, newswire, essays, journal articles, non-fiction, fiction, microphone speech, journal entries, meeting speech, microphone conversation, correspondence, transcribed speech, dictionaries|
|Application(s):||semantic role labelling|
|Online Documentation:||LDC2020T12 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Wang, Shichang, et al. SemTransCNC LDC2020T12. Web Download. Philadelphia: Linguistic Data Consortium, 2020.|
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.
Please view this text sample (CSV).
None at this time.