superlim-2 / README.md
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metadata
annotations_creators:
  - other
language:
  - sv
language_creators:
  - other
license: []
multilinguality:
  - monolingual
pretty_name: >-
  A standardized suite for evaluation and analysis of Swedish natural language
  understanding systems.
size_categories:
  - unknown
source_datasets: []
tags: []
task_categories:
  - multiple-choice
  - text-classification
  - question-answering
  - sentence-similarity
  - token-classification
task_ids:
  - sentiment-analysis
  - acceptability-classification
  - closed-domain-qa
  - word-sense-disambiguation
  - coreference-resolution

Dataset Card for [Dataset Name]

Table of Contents

Dataset Description

Dataset Summary

SuperLim 2.0 is a continuation of SuperLim 1.0, which aims for a standardized suite for evaluation and analysis of Swedish natural language understanding systems. The projects is inspired by the GLUE/SuperGLUE projects from which the name is derived: "lim" is the Swedish translation of "glue".

Supported Tasks and Leaderboards

[More Information Needed]

Languages

Swedish

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

All are test only, except for DaLAJ and ABSAbank which both have a train, dev and test split.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

To cite as a whole, use the standard reference. If you use or reference individual resources, cite the references specific for these resources:

Standard reference:

Yvonne Adesam, Aleksandrs Berdicevskis, Felix Morger (2020): [SwedishGLUE – Towards a Swedish Test Set for Evaluating Natural Language Understanding Models] (https://gup.ub.gu.se/publication/299130?lang=sv)

Dataset references:

[More information needed]

Thanks to Felix Morger for adding this dataset.