Papers › Using Wikipedia Edits in Low Resource Grammatical Error Correction
Using Wikipedia Edits in Low Resource Grammatical Error Correction
Adriane Boyd
We develop a grammatical error correction (GEC) system for German using a small gold GEC corpus augmented with edits extracted from Wikipedia revision history. We extend the automatic error annotation tool ERRANT (Bryant et al., 2017) for German and use it to analyze both gold GEC corrections and Wikipedia edits (Grundkiewicz and Junczys-Dowmunt, 2014) in order to select as additional training data Wikipedia edits containing grammatical corrections similar to those in the gold corpus. Using a multilayer convolutional encoder-decoder neural network GEC approach (Chollampatt and Ng, 2018), we evaluate the contribution of Wikipedia edits and find that carefully selected Wikipedia edits increase performance by over 5{\%}.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Grammatical Error Correction | Falko-MERLIN | Multilayer Convolutional Encoder-Decoder | F0.5 | 43.35 | #6 of 6 | Archive leaderboard | report |
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