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p-icl's Introduction

P-ICL

selection

Data Preparation

Please save your dataset in data folder. Note that CoNLL2003 and WNUT2017 are open-source datasets, ACE2004 and ACE2005 are not free. We keep our CoNLL2003 and WNUT2017 train and test JSON files in data folder.

Generation

Please review generate.py for P-ICL and utils.py for prompts, and change some important parameters.

python generate.py --dataset your_dataset --mode your_mode --picl_cnt your_picl_cnt --icl_cnt your_icl_cnt

Evaluation

Please review eval.py for computing entity-level F1 score.

python eval.py --label_path your_label_file_path --pred_path your_model_output_file_path

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