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Preposition Error Correction based on Automatically Extracted Grammar Patterns
Thesis

Preposition Error Correction based on Automatically Extracted Grammar Patterns

Chang, Shu Hao
Masters, 國立清華大學, 資訊工程學系
2014

Abstract

文法改錯 樣式文法 平行詞彙抽取 維基修改記錄語料庫 英國國家語料庫 機器翻譯 Grammar Error Correction Grammar Pattern Parallel Phrase Extraction Wikipedia Revision Corpus British National Corpus Machine Translation
In this paper, we introduce a new method for providing corrective feedback for preposition errors in learners' writing. In our approach, we extract Synchronous Grammar Patterns (SGP) for grammatical error correction (GEC) from a large error-annotated corpus. In addition, we also extract grammar patterns (GP) from a general English corpus to validate and supplement GEC patterns. The method involves automatically identifying syntactic patterns in the training data, automatically extracting distinct patterns with counts, and filtering and generating GEC patterns. At run-time, we identify grammar patterns in a given sentence. We apply our acquired GEC patterns to match the patterns in the given sentence and rank GEC patterns by frequency. We present \textit{WriteAhead}, a prototype system, that automatically extracts and displays relevant grammar error correction patterns with examples to prompt the user as they type or mouse around a draft. Preliminary experiments and evaluation results on a publicly available dataset, show our method works reasonably well for preposition errors.

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