annotations_creators:
- expert-generated
language_creators:
- other
language:
- sv
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids:
- named-entity-recognition
- part-of-speech
pretty_name: sucx3_ner
tags:
- structure-prediction
Dataset Card for SUCX 3.0 - NER
Dataset Description
- Homepage: https://spraakbanken.gu.se/en/resources/suc3
- Repository: https://github.com/kb-labb/sucx3_ner
- Paper: SUC 2.0 manual
- Point of Contact:
Dataset Summary
The dataset is a conversion of the venerable SUC 3.0 dataset into the huggingface ecosystem. The original dataset does not contain an official train-dev-test split, which is introduced here; the tag distribution for the NER tags between the three splits is mostly the same.
The dataset has three different types of tagsets: manually annotated POS, manually annotated NER, and automatically annotated NER. For the automatically annotated NER tags, only sentences were chosen, where the automatic and manual annotations would match (with their respective categories).
Additionally we provide remixes of the same data with some or all sentences being lowercased.
Supported Tasks and Leaderboards
- Part-of-Speech tagging
- Named-Entity-Recognition
Languages
Swedish
Dataset Structure
Data Remixes
original_tagscontain the manual NER annotationslowerthe whole dataset uncasedlower_mixsome of the dataset uncasedlower_bothevery instance both cased and uncased
simple_tagscontain the automatic NER annotationslowerthe whole dataset uncasedlower_mixsome of the dataset uncasedlower_bothevery instance both cased and uncased
Data Instances
For each instance, there is an id, with an optional _lower suffix to mark
that it has been modified, a tokens list of strings containing tokens, a
pos_tags list of strings containing POS-tags, and a ner_tags list of strings
containing NER-tags.
{"id": "e24d782c-e2475603_lower",
"tokens": ["-", "dels", "har", "vi", "inget", "index", "att", "g\u00e5", "efter", ",", "vi", "kr\u00e4ver", "allts\u00e5", "ers\u00e4ttning", "i", "40-talets", "penningv\u00e4rde", "."],
"pos_tags": ["MID", "KN", "VB", "PN", "DT", "NN", "IE", "VB", "PP", "MID", "PN", "VB", "AB", "NN", "PP", "NN", "NN", "MAD"],
"ner_tags": ["O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"]}
Data Fields
id: a string containing the sentence-idtokens: a list of strings containing the sentence's tokenspos_tags: a list of strings containing the tokens' POS annotationsner_tags: a list of strings containing the tokens' NER annotations
Data Splits
| Dataset Split | Size Percentage of Total Dataset Size | Number of Instances for the Original Tags |
|---|---|---|
| train | 64% | 46,026 |
| dev | 16% | 11,506 |
| test | 20% | 14,383 |
The simple_tags remix has fewer instances due to the requirement to match
tags.
Dataset Creation
See the original webpage
Additional Information
Dataset Curators
Licensing Information
CC BY 4.0 (attribution)
Citation Information
Contributions
Thanks to @robinqrtz for adding this dataset.