Judging Grammaticality with Count-Induced Tree Substitution Grammars
Francis Ferraro, Matt Post, Benjamin Van Durme, Durme Johns · 2013
Prior work has shown the utility of syntactic tree fragments as features in judging the grammaticality of text. To date such fragments have been extracted from derivations of Bayesianinduced Tree Substitution Grammars (TSGs). Evaluating on discriminative coarse and fine grammaticality classification tasks, we show that a simple, deterministic, count-based approach to fragment identification performs on par with the more complicated grammars of Post (2011). This represents a significant reduction in complexity for those interested in the use of such fragments in the development of systems for the educational domain. 1