Datasets:
Tasks:
Multiple Choice
Modalities:
Text
Formats:
parquet
Sub-tasks:
multiple-choice-qa
Languages:
English
Size:
10M - 100M
ArXiv:
License:
Commit
·
c7871a3
1
Parent(s):
e12fccd
Delete legacy dataset_infos.json
Browse files- dataset_infos.json +0 -59
dataset_infos.json
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{
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"default": {
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"description": "ASNQ is a dataset for answer sentence selection derived from\nGoogle's Natural Questions (NQ) dataset (Kwiatkowski et al. 2019).\n\nEach example contains a question, candidate sentence, label indicating whether or not\nthe sentence answers the question, and two additional features --\nsentence_in_long_answer and short_answer_in_sentence indicating whether ot not the\ncandidate sentence is contained in the long_answer and if the short_answer is in the candidate sentence.\n\nFor more details please see\nhttps://arxiv.org/pdf/1911.04118.pdf\n\nand\n\nhttps://research.google/pubs/pub47761/\n",
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"citation": "@article{garg2019tanda,\n title={TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection},\n author={Siddhant Garg and Thuy Vu and Alessandro Moschitti},\n year={2019},\n eprint={1911.04118},\n}\n",
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"homepage": "https://github.com/alexa/wqa_tanda#answer-sentence-natural-questions-asnq",
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"license": "",
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"features": {
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"question": {
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"dtype": "string",
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"_type": "Value"
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},
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"sentence": {
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"dtype": "string",
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"_type": "Value"
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},
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"label": {
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"names": [
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"neg",
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"pos"
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],
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"_type": "ClassLabel"
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},
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"sentence_in_long_answer": {
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"dtype": "bool",
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"_type": "Value"
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},
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"short_answer_in_sentence": {
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"dtype": "bool",
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"_type": "Value"
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}
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},
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"builder_name": "parquet",
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"dataset_name": "asnq",
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"config_name": "default",
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"version": {
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"version_str": "1.0.0",
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"major": 1,
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"minor": 0,
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"patch": 0
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},
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 3656865072,
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"num_examples": 20377568,
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"dataset_name": null
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},
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"validation": {
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"name": "validation",
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"num_bytes": 168004403,
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"num_examples": 930062,
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"dataset_name": null
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}
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},
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"download_size": 2496835395,
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"dataset_size": 3824869475,
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"size_in_bytes": 6321704870
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}
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}
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