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XGLUEPOS.py
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XGLUEPOS.py
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from llmebench.datasets.dataset_base import DatasetBase
from llmebench.tasks import TaskType
class XGLUEPOSDataset(DatasetBase):
def __init__(self, **kwargs):
super(XGLUEPOSDataset, self).__init__(**kwargs)
@staticmethod
def metadata():
return {
"language": "ar",
"citation": """@inproceedings{liang2020xglue,
title={XGLUE: A new benchmark datasetfor cross-lingual pre-training, understanding and generation},
author={Liang, Yaobo and Duan, Nan and Gong, Yeyun and Wu, Ning and Guo, Fenfei and Qi, Weizhen and Gong, Ming and Shou, Linjun and Jiang, Daxin and Cao, Guihong and others},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
pages={6008--6018},
year={2020}
}""",
"link": "https://microsoft.github.io/XGLUE/",
"license": "Non-commercial research purposes only",
"splits": {
"dev": "ar.dev.src-trg.txt",
"test": "ar.test.src-trg.txt",
},
"task_type": TaskType.SequenceLabeling,
"class_labels": [
"ADJ",
"ADP",
"ADV",
"AUX",
"CCONJ",
"DET",
"INTJ",
"NOUN",
"NUM",
"PART",
"PRON",
"PROPN",
"PUNCT",
"SYM",
"VERB",
"X",
],
}
@staticmethod
def get_data_sample():
return {
"input": "Original sentence",
"label": "Sentence with POS tags",
}
def load_data(self, data_path, no_labels=False):
data_path = self.resolve_path(data_path)
data = []
with open(data_path, "r") as fp:
for line_idx, line in enumerate(fp):
data.append(
{
"input": line.strip().split("\t")[0],
"label": line.strip().split("\t")[1],
"line_number": line_idx,
}
)
return data