SemTransCNC

<h3>Introduction</h3><br>
<p>SemTransCNC was developed by <a href="https://www.polyu.edu.hk/en/">The Hong Kong Polytechnic University</a>. It is comprised of a semantic transparency dataset of Chinese nominal compounds built using a series of crowd-based experiments.</p><br>
<p>Nominal compounds were selected from the <a href="https://ckip.iis.sinica.edu.tw/project/sinicacorpus/">Sinica Corpus</a> 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 <em>A</em> and <em>B</em> similar to the meaning of <em>AB</em>?" For assessing constituent semantic transparency (CST), they were asked to describe the similarity of <em>A</em> alone to its meaning in <em>AB</em> and the meaning of <em>B</em> alone to its meaning in <em>AB</em>.</p><br>
<h3>Data</h3><br>
<p>SemTransCNC consists of OST and CST data for 1,176 dimorphemic Chinese nominal compounds, which consist of free morphemes and have mid-range frequencies.</p><br>
<p>The text data is presented as a UTF-8 encoded comma separated text file.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2020T12.csv">text sample (CSV)</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2020 The Hong Kong Polytechnic University, © 2020 Trustees of the University of Pennsylvania