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README.md
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## Dataset Description
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- [**Paper:**](https://arxiv.org/pdf/2004.10645.pdf)
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### Dataset Summary
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### Supported Tasks and Leaderboards
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An example from the data set looks as follows:
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```
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{
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'The <b>first</b> season of the American animated <b>television</b> series The <b>Simpsons</b> \noriginally <b>aired</b> on the Fox network between December 17, 1989, and May 13, \n1990, beginning with the Christmas special "<b>Simpsons</b> Roasting on an Open Fire\n". The executive producers for the <b>first</b> production season <b>were</b> Matt Groening, ...',
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'The <b>Simpsons</b> is an American animated <b>television</b> sitcom created by Matt \nGroening for the Fox ... Since its <b>debut</b> on December 17, 1989, The <b>Simpsons</b> \n<b>has</b> broadcast 674 episodes. The show holds several American <b>television</b> \nlongevity ...',
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'The opening sequence of the American animated <b>television</b> series The <b>Simpsons</b> \nis among the most popular opening sequences in <b>television</b> and is accompanied \nby one of <b>television's</b> most recognizable theme songs. The <b>first</b> episode to use \nthis intro <b>was</b> the series' second episode "Bart the ... <b>was</b> the <b>first</b> episode of The \n<b>Simpsons</b> to <b>air</b> in 720p high-definition <b>television</b>, ...',
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'"<b>Simpsons</b> Roasting on an Open Fire", titled onscreen as "The <b>Simpsons</b> \nChristmas Special", is the premiere episode of the American animated <b>TV</b> series \nThe <b>Simpsons</b>, ... The show <b>was</b> originally intended to <b>debut</b> earlier in 1989 with "\nSome Enchanted Evening", but due to animation problems with that episode, the \nshow ...',
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'"Stark Raving Dad" is the <b>first</b> episode of the third season of the American \nanimated <b>television</b> series The <b>Simpsons</b>. It <b>first aired</b> on the Fox network in the \nUnited States on September 19, 1991. ... The <b>Simpsons was</b> the second highest \nrated show on Fox the week it <b>aired</b>, behind Married... with Children. "Stark \nRaving Dad," ...',
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'The <b>Simpsons</b>' twentieth season <b>aired</b> on Fox from September 28, 2008 to May \n17, 2009. With this season, the show tied Gunsmoke as the longest-running \nAmerican primetime <b>television</b> series in terms of total number ... It <b>was</b> the <b>first</b>-\never episode of the show to <b>air</b> in Europe before being seen in the United States.',
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'The animated <b>TV</b> show The <b>Simpsons</b> is an American English language \nanimated sitcom which ... The <b>Simpsons was</b> dubbed for the <b>first</b> time in Punjabi \nand <b>aired</b> on Geo <b>TV</b> in Pakistan. The name of the localised Punjabi version is \nTedi Sim ...'],
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'title': ['History of The Simpsons',
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'The Simpsons',
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'The Simpsons shorts',
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'The Simpsons (season 1)',
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'List of The Simpsons episodes',
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'The Simpsons opening sequence',
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'Simpsons Roasting on an Open Fire',
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'Stark Raving Dad',
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'The Simpsons (season 20)',
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'Non-English versions of The Simpsons']}]},
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'viewed_doc_titles': ['The Simpsons']}
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```
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### Data Fields
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```
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{'id': Value(dtype='string', id=None),
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'question': Value(dtype='string', id=None),
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'annotations': Sequence(feature={'type': Value(dtype='string', id=None), 'answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qaPairs': Sequence(feature={'question': Value(dtype='string', id=None), 'answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)}, length=-1, id=None)}, length=-1, id=None),
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'viewed_doc_titles': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None),
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'used_queries': Sequence(feature={'query': Value(dtype='string', id=None), 'results': Sequence(feature={'title': Value(dtype='string', id=None), 'snippet': Value(dtype='string', id=None)}, length=-1, id=None)}, length=-1, id=None),
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'nq_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None),
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'nq_doc_title': Value(dtype='string', id=None)}
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```
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In the original data format `annotations` have different keys depending on the `type` field = `singleAnswer` or `multipleQAs`. But this implementation uses an empty list `[]` for the unavailable keys
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please refer to Dataset Contents(https://github.com/shmsw25/AmbigQA#dataset-contents) for more details.
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```
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for example in train_light_dataset:
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for i,t in enumerate(example['annotations']['type']):
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if t =='singleAnswer':
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# use the example['annotations']['answer'][i]
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# example['annotations']['qaPairs'][i] - > is []
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print(example['annotations']['answer'][i])
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else:
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# use the example['annotations']['qaPairs'][i]
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# example['annotations']['answer'][i] - > is []
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print(example['annotations']['qaPairs'][i])
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```
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please refer to Dataset Contents(https://github.com/shmsw25/AmbigQA#dataset-contents) for more details.
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Light version only has `id`, `question`, `annotations` fields
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### Data Splits
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- train:
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## Dataset Creation
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## Dataset Description
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- [**Repository:**](https://github.com/apple/ml-qrecc)
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- [**Paper:**](https://arxiv.org/pdf/2010.04898.pdf)
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### Dataset Summary
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QReCC (Question Rewriting in Conversational Context) is an end-to-end open-domain question answering dataset comprising of 14K conversations with 81K question-answer pairs. The goal of this dataset is to provide a challenging benchmark for end-to-end conversational question answering that includes the individual subtasks of question rewriting, passage retrieval and reading comprehension.
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The task in QReCC is to find answers to conversational questions within a collection of 10M web pages split into 54M passages. Answers to questions in the same conversation may be distributed across several web pages.
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### Supported Tasks and Leaderboards
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An example from the data set looks as follows:
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```
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{
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"Context": [
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"What are the pros and cons of electric cars?",
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"Some pros are: They're easier on the environment. Electricity is cheaper than gasoline. Maintenance is less frequent and less expensive. They're very quiet. You'll get tax credits. They can shorten your commute time. Some cons are: Most EVs have pretty short ranges. Recharging can take a while."
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],
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"Question": "Tell me more about Tesla",
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"Rewrite": "Tell me more about Tesla the car company.",
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"Answer": "Tesla Inc. is an American automotive and energy company based in Palo Alto, California. The company specializes in electric car manufacturing and, through its SolarCity subsidiary, solar panel manufacturing.",
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"Answer_URL": "https://en.wikipedia.org/wiki/Tesla,_Inc.",
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"Conversation_no": 74,
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"Turn_no": 2,
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"Conversation_source": "trec"
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}
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```
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### Data Fields
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[More Information Needed]
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### Data Splits
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- train: 63501
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- test: 16451
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## Dataset Creation
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