Dataset Card for "squad_it"

Dataset Summary

SQuAD-it is derived from the SQuAD dataset and it is obtained through semi-automatic translation of the SQuAD dataset into Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian. The dataset contains more than 60,000 question/answer pairs derived from the original English dataset. The dataset is split into training and test sets to support the replicability of the benchmarking of QA systems:

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 8.78 MB
• Size of the generated dataset: 58.79 MB
• Total amount of disk used: 67.57 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "answers": "{\"answer_start\": [243, 243, 243, 243, 243], \"text\": [\"evitare di essere presi di mira dal boicottaggio\", \"evitare di essere pres...",
    "context": "\"La crisi ha avuto un forte impatto sulle relazioni internazionali e ha creato una frattura all' interno della NATO. Alcune nazi...",
    "id": "5725b5a689a1e219009abd28",
    "question": "Perchè le nazioni europee e il Giappone si sono separati dagli Stati Uniti durante la crisi?"
}

Data Fields

The data fields are the same among all splits.

default

• id : a string feature.
• context : a string feature.
• question : a string feature.
• answers : a dictionary feature containing:
  • text : a string feature.
  • answer_start : a int32 feature.

Data Splits

name	train	test
default	54159	7609

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@InProceedings{10.1007/978-3-030-03840-3_29,
    author="Croce, Danilo and Zelenanska, Alexandra and Basili, Roberto",
    editor="Ghidini, Chiara and Magnini, Bernardo and Passerini, Andrea and Traverso, Paolo",
    title="Neural Learning for Question Answering in Italian",
    booktitle="AI*IA 2018 -- Advances in Artificial Intelligence",
    year="2018",
    publisher="Springer International Publishing",
    address="Cham",
    pages="389--402",
    isbn="978-3-030-03840-3"
}

Contributions

Thanks to @thomwolf , @lewtun , @albertvillanova , @mariamabarham , @patrickvonplaten for adding this dataset.