DOI: 10.23695/zgkb-s720
title: Svensk EAT: frågeklassifikation
title: Swedish EAT: question classification

description: I. IDENTIFYING INFORMATION

Title*
Swedish EAT v1.0

Subtitle

Created by*
Jonatan Cerwall (jonatancerwall@gmail.com)

Publisher(s)*
Språkbanken Text

Link(s) / permanent identifier(s)*

License(s)*

Abstract*

      This dataset is a translated version of the QAQC dataset
      (https://cogcomp.seas.upenn.edu/Data/QA/QC/) for expected-answer-type
      classification. Taxonomy is the Li and Roth Taxonomy, also from
      https://cogcomp.seas.upenn.edu/Data/QA/QC/.

Funded by*

Cite as

      Cerwall, J. (2021). What the BERT? Fine-tuning KB-BERT for Question
      Classification. Unpublished manuscript, School of Electrical Engineering
      and Computer Science, KTH.

Related datasets

II. USAGE

Key applications
Machine learning, EAT Classification

Intended task(s)/usage(s)
Evaluate models by standard classification

Recommended evaluation measures
Accuracy

Dataset function(s)
Testing

Recommended split(s)
Test only

III. DATA

Primary data*
Text

Language*
Swedish

Dataset in numbers*
5451 questions in training set, 500 in test set.

Nature of the content*
Open ended factoid questions.

Format*
Comma-separated, four columns:

text -- the open ended factoid question

      verbose label -- both the coarse-grained label and the fine-grained label
      formatted as COARSE:fine

coarse label -- coarse-grained label

fine label -- fine-grained label

Data source(s)*

      Translated from the QAQC dataset
      (https://cogcomp.seas.upenn.edu/Data/QA/QC/)

Data collection method(s)*
--

Data selection and filtering*
--

Data preprocessing*
--

Data labeling*
--

Annotator characteristics

IV. ETHICS AND CAVEATS

Ethical considerations

      "Some outdated treatment of women (eg "Vilka är de sexigaste kvinnorna i
      världen?")"

Things to watch out for

V. ABOUT DOCUMENTATION

Data last updated*
2021-07-27

Which changes have been made, compared to the previous version*
First version

Access to previous versions

This document created*
2021-07-27

This document last updated*
2023-06-08

Where to look for further details

Documentation template version*

VI. OTHER

Related projects

References
description: I. IDENTIFYING INFORMATION

Title*
Swedish EAT v1.0

Subtitle

Created by*
Jonatan Cerwall (jonatancerwall@gmail.com)

Publisher(s)*
Språkbanken Text

Link(s) / permanent identifier(s)*

License(s)*

Abstract*

      This dataset is a translated version of the QAQC dataset
      (https://cogcomp.seas.upenn.edu/Data/QA/QC/) for expected-answer-type
      classification. Taxonomy is the Li and Roth Taxonomy, also from
      https://cogcomp.seas.upenn.edu/Data/QA/QC/.

Funded by*

Cite as

      Cerwall, J. (2021). What the BERT? Fine-tuning KB-BERT for Question
      Classification. Unpublished manuscript, School of Electrical Engineering
      and Computer Science, KTH.

Related datasets

II. USAGE

Key applications
Machine learning, EAT Classification

Intended task(s)/usage(s)
Evaluate models by standard classification

Recommended evaluation measures
Accuracy

Dataset function(s)
Testing

Recommended split(s)
Test only

III. DATA

Primary data*
Text

Language*
Swedish

Dataset in numbers*
5451 questions in training set, 500 in test set.

Nature of the content*
Open ended factoid questions.

Format*
Comma-separated, four columns:

text -- the open ended factoid question

      verbose label -- both the coarse-grained label and the fine-grained label
      formatted as COARSE:fine

coarse label -- coarse-grained label

fine label -- fine-grained label

Data source(s)*

      Translated from the QAQC dataset
      (https://cogcomp.seas.upenn.edu/Data/QA/QC/)

Data collection method(s)*
--

Data selection and filtering*
--

Data preprocessing*
--

Data labeling*
--

Annotator characteristics

IV. ETHICS AND CAVEATS

Ethical considerations

      "Some outdated treatment of women (eg "Vilka är de sexigaste kvinnorna i
      världen?")"

Things to watch out for

V. ABOUT DOCUMENTATION

Data last updated*
2021-07-27

Which changes have been made, compared to the previous version*
First version

Access to previous versions

This document created*
2021-07-27

This document last updated*
2023-06-08

Where to look for further details

Documentation template version*

VI. OTHER

Related projects

References