Paper: A Comparative Evaluation of Deep and Shallow Approaches to the Automatic Detection of Common Grammatical Errors

ACL ID D07-1012
Title A Comparative Evaluation of Deep and Shallow Approaches to the Automatic Detection of Common Grammatical Errors
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

This paper compares a deep and a shallow processing approach to the problem of clas- sifying a sentence as grammatically well- formed or ill-formed. The deep processing approach uses the XLE LFG parser and En- glish grammar: two versions are presented, one which uses the XLE directly to perform the classification, and another one which uses a decision tree trained on features con- sisting of the XLE’s output statistics. The shallow processing approach predicts gram- maticality based on n-gram frequency statis- tics: we present two versions, one which uses frequency thresholds and one which uses a decision tree trained on the frequen- cies of the rarest n-grams in the input sen- tence. We find that the use of a decision tree improves on the basic approach only for the deep parser-based ap...