Is Argument Structure of Learner Chinese Understandable: A Corpus-Based Analysis
This work addresses the problem of analyzing language learner errors for educators and linguists, but it is incremental as it applies an existing method to new data.
The paper tackled the problem of understanding argument structure errors in learner Chinese by conducting a corpus-based analysis using manually annotated semantic role labeling, and found that the Chinese PropBank specification is comprehensive for second language phenomena with high inter-annotator agreement.
This paper presents a corpus-based analysis of argument structure errors in learner Chinese. The data for analysis includes sentences produced by language learners as well as their corrections by native speakers. We couple the data with semantic role labeling annotations that are manually created by two senior students whose majors are both Applied Linguistics. The annotation procedure is guided by the Chinese PropBank specification, which is originally developed to cover first language phenomena. Nevertheless, we find that it is quite comprehensive for handling second language phenomena. The inter-annotator agreement is rather high, suggesting the understandability of learner texts to native speakers. Based on our annotations, we present a preliminary analysis of competence errors related to argument structure. In particular, speech errors related to word order, word selection, lack of proposition, and argument-adjunct confounding are discussed.