Datasets:
lmqg
/

Modalities:
Text
Sub-tasks:
extractive-qa
Languages:
English
ArXiv:
Libraries:
Datasets
License:
asahi417 commited on
Commit
3b31cf0
1 Parent(s): 0eddab4
Files changed (3) hide show
  1. README.md +0 -2
  2. process.py +26 -0
  3. qa_squad.py +14 -20
README.md CHANGED
@@ -51,7 +51,6 @@ The data fields are the same among all splits.
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  ## Citation Information
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  ```
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-
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  @article{2016arXiv160605250R,
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  author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
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  Konstantin and {Liang}, Percy},
@@ -63,5 +62,4 @@ The data fields are the same among all splits.
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  archivePrefix = {arXiv},
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  eprint = {1606.05250},
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  }
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-
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  ```
 
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  ## Citation Information
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  ```
 
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  @article{2016arXiv160605250R,
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  author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
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  Konstantin and {Liang}, Percy},
 
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  archivePrefix = {arXiv},
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  eprint = {1606.05250},
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  }
 
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  ```
process.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import os
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+ import json
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+ from datasets import load_dataset
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+
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+ os.makedirs('datasets', exist_ok=True)
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+
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+ data = load_dataset("lmqg/qg_squad")
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+ _id = 0
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+ for _split in data:
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+ output = []
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+ for d in data[_split]:
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+ a = d['answer']
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+ p = d['paragraph']
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+ output.append({
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+ "id": str(_id),
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+ "title": "None",
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+ "context": d['paragraph'],
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+ "question": d['question'],
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+ "answers": {
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+ "text": [a],
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+ "answer_start": [p.index(a)]
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+ }
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+ })
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+ _id += 1
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+ with open(f'datasets/{_split}.jsonl', 'w') as f:
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+ f.write('\n'.join([json.dumps(i) for i in output]))
qa_squad.py CHANGED
@@ -8,27 +8,21 @@ _VERSION = "0.0.0"
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  _NAME = "qa_squad"
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  _DESCRIPTION = """SQuAD with the train/validation/test split used in SQuAD QG"""
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  _CITATION = """
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- @inproceedings{du-cardie-2018-harvesting,
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- title = "Harvesting Paragraph-level Question-Answer Pairs from {W}ikipedia",
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- author = "Du, Xinya and
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- Cardie, Claire",
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- booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
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- month = jul,
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- year = "2018",
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- address = "Melbourne, Australia",
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- publisher = "Association for Computational Linguistics",
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- url = "https://aclanthology.org/P18-1177",
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- doi = "10.18653/v1/P18-1177",
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- pages = "1907--1917",
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- abstract = "We study the task of generating from Wikipedia articles question-answer pairs that cover content beyond a single sentence. We propose a neural network approach that incorporates coreference knowledge via a novel gating mechanism. As compared to models that only take into account sentence-level information (Heilman and Smith, 2010; Du et al., 2017; Zhou et al., 2017), we find that the linguistic knowledge introduced by the coreference representation aids question generation significantly, producing models that outperform the current state-of-the-art. We apply our system (composed of an answer span extraction system and the passage-level QG system) to the 10,000 top ranking Wikipedia articles and create a corpus of over one million question-answer pairs. We provide qualitative analysis for the this large-scale generated corpus from Wikipedia.",
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  }
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  """
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- _BASE_URL = "https://huggingface.co/datasets/lmqg/qa_squad/resolve/main/dataset"
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- _URLS = {
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- str(datasets.Split.TRAIN): f'{_BASE_URL}/train.json',
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- str(datasets.Split.VALIDATION): f'{_BASE_URL}/dev.json',
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- str(datasets.Split.TEST): f'{_BASE_URL}/test.json'
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- }
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  class QASquadConfig(datasets.BuilderConfig):
@@ -104,4 +98,4 @@ class QASquad(datasets.GeneratorBasedBuilder):
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  "text": answers,
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  },
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  }
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- key += 1
 
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  _NAME = "qa_squad"
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  _DESCRIPTION = """SQuAD with the train/validation/test split used in SQuAD QG"""
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  _CITATION = """
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+ @article{2016arXiv160605250R,
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+ author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
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+ Konstantin and {Liang}, Percy},
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+ title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
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+ journal = {arXiv e-prints},
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+ year = 2016,
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+ eid = {arXiv:1606.05250},
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+ pages = {arXiv:1606.05250},
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+ archivePrefix = {arXiv},
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+ eprint = {1606.05250},
 
 
 
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  }
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  """
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+ _BASE_URL = "https://huggingface.co/datasets/lmqg/qa_squad/resolve/main/datasets"
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+ _URLS = {k: f'{_BASE_URL}/{k}.json' for k in
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+ [str(datasets.Split.TEST), str(datasets.Split.TRAIN), str(datasets.Split.VALIDATION)]}
 
 
 
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  class QASquadConfig(datasets.BuilderConfig):
 
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  "text": answers,
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  },
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  }
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+ key += 1