Comparison of various machine learning-based classifications of relative clauses
Mi-Young Kim · 2006
The detection of a gap in relative clauses is essential in syntactic and semantic analysis of natural language processing. This paper proposes automatic relative clause classification method based on various machine learning algorithms, and compare the classification performances of relative clauses. We use easily obtainable features that can be extracted from any language. We also analyze the contribution of each feature to the performance.