Datasets:
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
Dataset Card Creation Guide
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: N/A
- Repository: GitHub
- Paper: A Fine-grained Sentiment Dataset for Norwegian
- Leaderboard: N/A
- Point of Contact: -
Dataset Summary
Aggregated NoRec_fine: A Fine-grained Sentiment Dataset for Norwegian. This dataset was created by the Nordic Language Processing Laboratory by aggregating the fine-grained annotations in NoReC_fine and removing sentences with conflicting or no sentiment.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The text in the dataset is in Norwegian.
Dataset Structure
Data Instances
Example of one instance in the dataset.
{'label': 0, 'text': 'Verre er det med slagsmålene .'}
Data Fields
id
: index of the exampletext
: Text of a sentencelabel
: The sentiment label. Here- 0 = negative
- 1 = positive
Data Splits
The dataset is split into a train
, validation
, and test
split with the following sizes:
Tain | Valid | Test | |
---|---|---|---|
Number of examples | 2675 | 516 | 417 |
Dataset Creation
This dataset is based largely on the original data described in the paper A Fine-Grained Sentiment Dataset for Norwegian by L. Øvrelid, P. Mæhlum, J. Barnes, and E. Velldal, accepted at LREC 2020, paper available. However, we have since added annotations for another 3476 sentences, increasing the overall size and scope of the dataset.
Additional Information
Licensing Information
This work is licensed under a Creative Commons Attribution 4.0 International License
Citation Information
@misc{sheng2020investigating,
title={Investigating Societal Biases in a Poetry Composition System},
author={Emily Sheng and David Uthus},
year={2020},
eprint={2011.02686},
archivePrefix={arXiv},
primaryClass={cs.CL}
}