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Abstract Issues concerning relative clauses have attracted considerable attention in research areas such as theoretical linguistics, psycholinguistics, computational linguistics, and language acquisition and teaching. However, the size of research in previous studies was limited because it is time-consuming and error prone for researchers to extract and annotate relative clauses manually. To address this issue, a recent computer program named AutoSubClause, using dependency parsing, was developed to automatically extract and annotate different types of English subordinate clauses, but its performance remains unknown. In this study, we evaluate the accuracy of the program based on different types of texts including political and literary, written and spoken ones, produced by native speakers, learners, or translators, respectively. We also assess the reliability of its annotation of linguistic features such as accessibility, animacy, and restrictiveness. Results revealed an overall high performance on the extraction of relative clauses from native and translated texts, but the precision for learner’s texts need to be improved. In addition, the program demonstrated a high precision in the automatic annotation of linguistic features such as animacy, restrictiveness, and the roles of head nouns in relative clauses. Limitations of the pro- gram are discussed and suggestions for improvement are provided.
Key words: AutoSubClause; relative clauses; automatic extraction and annotation; multitype texts
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