Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
question-generation
License:
Update qg_tweetqa.py
Browse files- qg_tweetqa.py +22 -13
qg_tweetqa.py
CHANGED
@@ -2,13 +2,23 @@ import json
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_VERSION = "
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_NAME = "
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_CITATION = """
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"""
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_DESCRIPTION = """Question
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_URL = "https://huggingface.co/datasets/lmqg/
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_URLS = {
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'train': f'{_URL}/train.jsonl',
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'test': f'{_URL}/test.jsonl',
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@@ -16,7 +26,7 @@ _URLS = {
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}
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class
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"""BuilderConfig"""
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def __init__(self, **kwargs):
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@@ -24,13 +34,13 @@ class QAGTweetQAConfig(datasets.BuilderConfig):
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(
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class
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BUILDER_CONFIGS = [
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]
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def _info(self):
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@@ -38,11 +48,10 @@ class QAGTweetQA(datasets.GeneratorBasedBuilder):
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"
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"
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"paragraph": datasets.Value("string"),
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"paragraph_id": datasets.Value("string"),
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"questions_answers": datasets.Value("string")
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}
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),
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supervised_keys=None,
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_VERSION = "3.0.0"
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_NAME = "qg_tweetqa"
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_CITATION = """
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
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author = "Ushio, Asahi and
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Alva-Manchego, Fernando and
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Camacho-Collados, Jose",
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booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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year = "2022",
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address = "Abu Dhabi, U.A.E.",
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publisher = "Association for Computational Linguistics",
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}
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"""
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_DESCRIPTION = """Question generation dataset based on [TweetQA](https://huggingface.co/datasets/tweet_qa)."""
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_URL = "https://huggingface.co/datasets/lmqg/qg_tweetqa/resolve/main/data/processed"
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_URLS = {
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'train': f'{_URL}/train.jsonl',
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'test': f'{_URL}/test.jsonl',
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}
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class QGTweetQAConfig(datasets.BuilderConfig):
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"""BuilderConfig"""
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def __init__(self, **kwargs):
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(QGTweetQAConfig, self).__init__(**kwargs)
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class QGTweetQA(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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QGTweetQAConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
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]
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def _info(self):
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"answer": datasets.Value("string"),
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"paragraph_question": datasets.Value("string"),
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"question": datasets.Value("string"),
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"paragraph": datasets.Value("string"),
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}
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),
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supervised_keys=None,
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