| import os | |
| import json | |
| from datasets import load_dataset | |
| os.makedirs("data/tweet_ner7", exist_ok=True) | |
| data = load_dataset("tner/tweetner7") | |
| def process(tmp): | |
| tmp = [i.to_dict() for _, i in tmp.iterrows()] | |
| for i in tmp: | |
| i.pop("id") | |
| i['gold_label_sequence'] = i.pop('tags').tolist() | |
| i['text_tokenized'] = i.pop('tokens').tolist() | |
| i['text'] = ' '.join(i['text_tokenized']) | |
| return tmp | |
| train = process(data["train_2020"].to_pandas()) | |
| val = process(data["validation_2020"].to_pandas()) | |
| test = process(data["test_2021"].to_pandas()) | |
| with open("data/tweet_ner7/train.jsonl", "w") as f: | |
| f.write("\n".join([json.dumps(i) for i in train])) | |
| with open("data/tweet_ner7/validation.jsonl", "w") as f: | |
| f.write("\n".join([json.dumps(i) for i in val])) | |
| with open("data/tweet_ner7/test.jsonl", "w") as f: | |
| f.write("\n".join([json.dumps(i) for i in test])) | |