Datasets and codes for the paper "TGEA 2.0: A Large-Scale Diagnostically Annotated Dataset with Benchmark Tasks for Text Generation of Pretrained Language Models".

Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. (License URL: https://creativecommons.org/licenses/by-sa/4.0/)

Converting raw data to the format of each task

unzip data.zip
python data/convert_raw_data_to_benchmarks.py 
python data/convert_gec_format.py

1. Erroneous Text Detection

sh Diagnosis_tasks/train_b1.sh

2. MiSEW Extraction

sh Diagnosis_tasks/train_b2.sh

3. Erroneous Span Location

sh Diagnosis_tasks/train_b3.sh

4. Error Type Classification

sh Diagnosis_tasks/train_b4.sh

5. Error Correction

sh Diagnosis_tasks/train_b5.sh

m2scorer is used to evaluate results of error correction.

6. Generation Pathology Mitigation

sh Generation_Pathology_Mitigation/train_b6.sh
python Generation_Pathology_Mitigation/evaluate.py