task_categories:question-answering task_ids:open-domain-qa task_ids:extractive-qa annotations_creators:machine-generated language_creators:machine-generated multilinguality:monolingual size_categories:unknown source_datasets:extended|squad language:it license:unknown region:us
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:
@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}
}
---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- it
language_bcp47:
- it-IT
license:
- unknown
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- extended|squad
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
paperswithcode_id: squad-it
pretty_name: SQuAD-it
dataset_info:
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
    - name: answer_start
      dtype: int32
  splits:
  - name: train
    num_bytes: 50864824
    num_examples: 54159
  - name: test
    num_bytes: 7858336
    num_examples: 7609
  download_size: 8776531
  dataset_size: 58723160
---

# Dataset Card for "squad_it"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://github.com/crux82/squad-it](https://github.com/crux82/squad-it)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 8.78 MB
- **Size of the generated dataset:** 58.79 MB
- **Total amount of disk used:** 67.57 MB

### 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

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## 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

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 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](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@albertvillanova](https://github.com/albertvillanova), [@mariamabarham](https://github.com/mariamabarham), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.