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--- |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- found |
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language: |
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- no |
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license: |
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- cc-by-4.0 |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 1K<n<10K |
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source_datasets: |
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- original |
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task_categories: |
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- text-classification |
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--- |
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# Dataset Card Creation Guide |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-instances) |
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- [Data Splits](#data-instances) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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## Dataset Description |
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- **Homepage:** N/A |
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- **Repository:** [GitHub](https://github.com/ltgoslo/NorBERT/) |
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- **Paper:** N/A |
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- **Leaderboard:** N/A |
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- **Point of Contact:** - |
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### Dataset Summary |
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This is a classification dataset created from a subset of the [Talk of Norway](https://www.nb.no/sprakbanken/ressurskatalog/oai-repo-clarino-uib-no-11509-123/). This dataset contains text phrases from the political parties Fremskrittspartiet and Sosialistisk Venstreparti. The dataset is annotated with the party the speaker, as well as a timestamp. The classification task is to, simply by looking at the text, being able to predict is the speech was done by a representative from Fremskrittspartiet or from SV. |
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### Supported Tasks and Leaderboards |
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This dataset is meant for classification. Results can for instance be viewed in [this article](https://arxiv.org/abs/2104.09617). |
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### Languages |
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The text in the dataset is in Norwegian. |
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## Dataset Structure |
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### Data Instances |
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Example of one instance in the dataset. |
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```{'label': 0, 'text': 'Verre er det med slagsmålene .', 'date': '2016-01-15'}``` |
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### Data Fields |
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- `id`: index of the example |
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- `text`: Text of a speech |
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- `date`: Date (`YYYY-MM-DD`) the speech was produced |
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- `label`: Political party the speaker was associated with at the time |
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- 0 = Fremskrittspartiet |
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- 1 = Sosialistisk Venstreparti |
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### Data Splits |
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The dataset is split into a `train`, `validation`, and `test` split with the following sizes: |
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| | Tain | Valid | Test | |
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| ----- | ------ | ----- | ----- | |
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| Number of examples | 3600 | 1200 | 1200 | |
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The dataset is balanced on political party. |
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## Dataset Creation |
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This dataset is based on the publicly available information by Norwegian Parliament (Storting) and created by the National Library of Norway AI-Lab to benchmark their language models. |
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## Additional Information |
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The [Talk of Norway dataset] is also available [here](https://www.nb.no/sprakbanken/ressurskatalog/oai-repo-clarino-uib-no-11509-123/). |
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### Licensing Information |
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This work is licensed under a Creative Commons Attribution 4.0 International License. |
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### Citation Information |
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The following article can be quoted when referring to this dataset, since it is the first study that are using the dataset for evaluating a language model: |
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``` |
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@inproceedings{kummervold-etal-2021-operationalizing, |
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title = {Operationalizing a National Digital Library: The Case for a {N}orwegian Transformer Model}, |
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author = {Kummervold, Per E and |
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De la Rosa, Javier and |
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Wetjen, Freddy and |
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Brygfjeld, Svein Arne", |
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booktitle = {Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)}, |
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year = "2021", |
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address = "Reykjavik, Iceland (Online)", |
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publisher = {Link{"o}ping University Electronic Press, Sweden}, |
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url = "https://aclanthology.org/2021.nodalida-main.3", |
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pages = "20--29", |
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abstract = "In this work, we show the process of building a large-scale training set from digital and digitized collections at a national library. |
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The resulting Bidirectional Encoder Representations from Transformers (BERT)-based language model for Norwegian outperforms multilingual BERT (mBERT) models |
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in several token and sequence classification tasks for both Norwegian Bokm{aa}l and Norwegian Nynorsk. Our model also improves the mBERT performance for other |
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languages present in the corpus such as English, Swedish, and Danish. For languages not included in the corpus, the weights degrade moderately while keeping strong multilingual properties. Therefore, |
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we show that building high-quality models within a memory institution using somewhat noisy optical character recognition (OCR) content is feasible, and we hope to pave the way for other memory institutions to follow.", |
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} |
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``` |