ilmariky/SQuAD_v2_fi

---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- found
language:
- fi
license:
- gpl-3.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- question-answering
task_ids:
- extractive-qa
pretty_name: SQuAD-v2-fi
tags:
- question-generation
train-eval-index:
- config: plain_text
task: question-answering
task_id: extractive_question_answering
splits:
train_split: train
eval_split: validation
col_mapping:
question: question
context: context
answers:
text: text
answer_start: answer_start
---
# Dataset Card for "squad-v2-fi"
### Dataset Summary
Machine translated and normalized Finnish version of the SQuAD-v2.0 dataset. Details about the translation and normalization processes can be found [here](https://helda.helsinki.fi/handle/10138/344973).

Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
## Dataset Structure
### Data Instances
Example data:
```
{
"title": "Josefina (Ruotsin kuningatar)",
"paragraphs": [
{
"qas": [
{
"question": "Milloin Josefina Maximiliana Eugenia Napoleona av Leuchtenberg syntyi?",
"id": "2149392872931478957",
"answers": [
{
"answer_start": 59,
"text": "14. maaliskuuta 1807"
}
],
"is_impossible": false
}
],
"context": "Josefina Maximiliana Eugenia Napoleona av Leuchtenberg (14. maaliskuuta 1807 − 7. kesäkuuta 1876, Tukholma) oli Ruotsi-Norjan kuningatar ja kuningas Oskar I:n puoliso."
}
]
}
```
### Data Fields
The data fields are the same among all splits.
#### plain_text
- `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
| name |train|validation|
|----------|----:|---------:|
|plain_text|92383| 8737|

### Citation Information
```
@MastersThesis{3241c198b3f147faacbc6d8b64ed9419,
author = "Kylli{\"a}inen, {Ilmari}",
title = "Neural Factoid Question Answering and Question Generation for Finnish",
language = "en",
address = "Helsinki, Finland",
school = "University of Helsinki",
year = "2022",
month = "jun",
day = "15",
url = "https://helda.helsinki.fi/handle/10138/344973"
}
```

原始信息汇总

数据集卡片 "squad-v2-fi"

数据集概述

机器翻译和规范化后的芬兰语版本的SQuAD-v2.0数据集。

数据集结构

数据实例

示例数据： json { "title": "Josefina (Ruotsin kuningatar)", "paragraphs": [ { "qas": [ { "question": "Milloin Josefina Maximiliana Eugenia Napoleona av Leuchtenberg syntyi?", "id": "2149392872931478957", "answers": [ { "answer_start": 59, "text": "14. maaliskuuta 1807" } ], "is_impossible": false } ], "context": "Josefina Maximiliana Eugenia Napoleona av Leuchtenberg (14. maaliskuuta 1807 − 7. kesäkuuta 1876, Tukholma) oli Ruotsi-Norjan kuningatar ja kuningas Oskar I:n puoliso." } ] }

数据字段

所有分割的数据字段相同。

plain_text

• id: 字符串特征。
• title: 字符串特征。
• context: 字符串特征。
• question: 字符串特征。
• answers: 包含以下内容的字典特征：
  • text: 字符串特征。
  • answer_start: 整数特征。

数据分割

name	train	validation
plain_text	92383	8737

引用信息

plaintext @MastersThesis{3241c198b3f147faacbc6d8b64ed9419, author = "Kylli{"a}inen, {Ilmari}", title = "Neural Factoid Question Answering and Question Generation for Finnish", language = "en", address = "Helsinki, Finland", school = "University of Helsinki", year = "2022", month = "jun", day = "15", url = "https://helda.helsinki.fi/handle/10138/344973" }