---
language:
- tr
license:
- cc-by-sa-4.0
annotations_creators:
- machine-generated
language_creators:
- machine-generated
multilinguality:
- monolingual
pretty_name: SQuAD-TR
size_categories:
- 100K<n<1M
source_datasets:
- extended|squad
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
paperswithcode_id: squad-tr
configs:
- default
- excluded
- openqa

dataset_info:
- config_name: default
  features:
  - name: id
    dtype: string
  - name: title
    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: 95795325
    num_examples: 104791
  - name: validation
    num_bytes: 8287109
    num_examples: 8291
  download_size: 9425486
  dataset_size: 104082434
- config_name: excluded
  features:
  - name: id
    dtype: string
  - name: title
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
  splits:
  - name: train
    num_bytes: 24130226
    num_examples: 25528
  - name: validation
    num_bytes: 3427513
    num_examples: 3582
  download_size: 5270628
  dataset_size: 27557739
- config_name: openqa
  features:
  - name: id
    dtype: string
  - name: title
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    sequence:
    - name: text
      dtype: string
  splits:
  - name: train
    num_bytes: 119261215
    num_examples: 130319
  - name: validation
    num_bytes: 11649046
    num_examples: 11873
  download_size: 14696114
  dataset_size: 130910261
---
# Dataset Card for SQuAD-TR

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
- [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)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)

## Dataset Description

- **Repository:** [SQuAD-TR GitHub Repository](https://github.com/boun-tabi/SQuAD2.0-TR)
- **Paper:** Building Efficient and Effective OpenQA Systems for Low-Resource Languages
- **Point of Contact:** [Emrah Budur](mailto:emrah.budur@boun.edu.tr)

### Dataset Summary

SQuAD-TR is a machine translated version of the original SQuAD2.0 dataset into Turkish, using "Amazon Translate".

## Dataset Structure

### Data Instances

Our data instances follow that of the original SQuAD2.0 dataset.
Shared below is an example instance from the default train dataset.

```
{
    "id": "56be85543aeaaa14008c9063",
    "title": "Beyonce",
    "context": "Beyoncé Giselle Knowles-Carter (d. 4 Eylül 1981), ABD'li şarkıcı, söz yazarı, prodüktör ve aktris. Houston, Teksas'ta doğup büyüdü, çocukken çeşitli şarkı ve dans yarışmalarında sahne aldı ve 1990'ların sonlarında R&B kız grubu Destiny's Child'ın solisti olarak ün kazandı. Babası Mathew Knowles tarafından yönetilen grup tüm zamanların en çok satan kız gruplarından biri oldu. Beyoncé'nin ilk albümü Dangerously in Love'ın (2003) yayınlanmasını izlemiştir ve beş Grammy Ödülü kazanmış ve Billboard Hot 100 bir numaralı single'ları “Crazy in Love” ve “Baby Boy\"un yer aldığı Beyoncé'nin ilk albümü Dangerously in Love (2003) yayınlandı.",
    "question": "Beyonce ne zaman popüler olmaya başladı?",
    "answers": [
      {
        "text": "1990'ların sonlarında",
        "answer_start": 192
      }
    ]
}

```
Notes:
- The training split we get by `openqa` parameter will not include `answer_start` field as it is not required for the training phase of the OpenQA formulation.
- The split we get by `excluded` parameter is also missing `answer_start` field as we could not identify the starting index of the answers for these examples from the context after the translation.

### Data Fields

The data fields with `*` prefix are the same for all splits. The splits we get by `openqa` and `excluded` parameters are missing `answer_start` field. 

- `*id`: a string feature.
- `*title`: 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

The SQuAD2.0 TR dataset has 2 splits: _train_ and _validation_. Below are the statistics for the most recent version of the dataset in the default configuration.

| Split      | Articles | Paragraphs | Answerable Questions | Unanswerable Questions | Total   |
| ---------- | -------- | ---------- | -------------------- | ---------------------- | ------- |
| train      | 442      | 18776      | 61293                | 43498                  | 104,791 |
| validation | 35       | 1204       | 2346                 | 5945                   | 8291    |

In addition to the default configuration, we also include a different view of train split specifically for openqa setting. In this setting, we only provide question-answer pairs along with their contexts.  

| Split      | Articles | Paragraphs | Questions w/ answers |  Total   |
| ---------- | -------- | ---------- | -------------------- |  ------- |
| openqa     | 442      | 18776      | 86821                |  86821   |



## Dataset Creation

### Curation Rationale

We translated the titles, context paragraphs, questions and answer spans from the original SQuAD2.0 dataset using "Amazon Translate" - requiring us to remap the starting positions of the answer spans, since their positions were changed due to the automatic translation.
We performed an automatic post-processing step to populate the start positions for the answer spans.
To do so, we have first looked at whether there was an exact match for the translated answer span in the translated context paragraph and if so, we kept the answer text along with this start position found.
If no exact match was found, we looked for approximate matches using a character-level edit distance algorithm.
We have excluded the question-answer pairs from the original dataset where neither an exact nor an approximate match was found in the translated version.
Our "default" configuration corresponds to this version.
We have put the "excluded" examples in our "excluded" configuration.
As a result, the datasets in these two configurations are mutually exclusive.

| Split   | Articles | Paragraphs | Questions wo/ answers | Total   |
| ------- | -------- | ---------- | --------------------- | ------- |
| train   | ?        | ?          | 25528                 | 25528   |
| dev     | ?        | ?          | ?                     | ?       |


More information on our translation strategy can be found in our linked paper.

### Source Data

This dataset used the original SQuAD2.0 dataset as its source data.

### Licensing Information

The SQuAD-TR is released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) in accordance with the license of SQuAD-2.0. 

### Citation Information

```
@article{[TODO Emrah]}
```