Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Multilinguality:
multilingual
Size Categories:
n<1K
Tags:
License:
| dataset_info: | |
| features: | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: string | |
| - name: url | |
| dtype: string | |
| splits: | |
| - name: test_de | |
| num_bytes: 164433 | |
| num_examples: 200 | |
| - name: test_fr | |
| num_bytes: 186036 | |
| num_examples: 200 | |
| - name: test_it | |
| num_bytes: 197513 | |
| num_examples: 200 | |
| - name: test_rm | |
| num_bytes: 206644 | |
| num_examples: 200 | |
| download_size: 220352 | |
| dataset_size: 754626 | |
| license: cc-by-4.0 | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| language: | |
| - de | |
| - fr | |
| - it | |
| - rm | |
| multilinguality: | |
| - multilingual | |
| pretty_name: SwissNER | |
| size_categories: | |
| - n<1K | |
| # SwissNER | |
| A multilingual test set for named entity recognition (NER) on Swiss news articles. | |
| ## Description | |
| SwissNER is a dataset for named entity recognition based on manually annotated news articles in Swiss Standard German, French, Italian, and Romansh Grischun. | |
| We have manually annotated a selection of articles that have been published in February 2023 in the categories "Switzerland" or "Regional" on the following online news portals: | |
| - Swiss Standard German: [srf.ch](https://www.srf.ch/) | |
| - French: [rts.ch](https://www.rts.ch/) | |
| - Italian: [rsi.ch](https://www.rsi.ch/) | |
| - Romansh Grischun: [rtr.ch](https://www.rtr.ch/) | |
| For each article we extracted the first two paragraphs after the lead paragraph. | |
| We followed the guidelines of the CoNLL-2002 and 2003 shared tasks and annotated the names of persons, organizations, locations and miscellaneous entities. | |
| The annotation was performed by a single annotator. | |
| When using this dataset, please consider citing our paper, ["SwissBERT: The Multilingual Language Model for Switzerland"](https://aclanthology.org/2023.swisstext-1.6/) (SwissText 2023). | |
| ## License | |
| - Text paragraphs: © Swiss Broadcasting Corporation (SRG SSR) | |
| - Annotations: Attribution 4.0 International (CC BY 4.0) | |
| ## Statistics | |
| | | DE | FR | IT | RM | Total | | |
| |----------------------|-----:|------:|------:|------:|------:| | |
| | Number of paragraphs | 200 | 200 | 200 | 200 | 800 | | |
| | Number of tokens | 9498 | 11434 | 12423 | 13356 | 46711 | | |
| | Number of entities | 479 | 475 | 556 | 591 | 2101 | | |
| | – `PER` | 104 | 92 | 93 | 118 | 407 | | |
| | – `ORG` | 193 | 216 | 266 | 227 | 902 | | |
| | – `LOC` | 182 | 167 | 197 | 246 | 792 | | |
| | – `MISC` | 113 | 79 | 88 | 39 | 319 | | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{vamvas-etal-2023-swissbert, | |
| title = "{S}wiss{BERT}: The Multilingual Language Model for {S}witzerland", | |
| author = {Vamvas, Jannis and | |
| Gra{\"e}n, Johannes and | |
| Sennrich, Rico}, | |
| editor = {Ghorbel, Hatem and | |
| Sokhn, Maria and | |
| Cieliebak, Mark and | |
| H{\"u}rlimann, Manuela and | |
| de Salis, Emmanuel and | |
| Guerne, Jonathan}, | |
| booktitle = "Proceedings of the 8th edition of the Swiss Text Analytics Conference", | |
| month = jun, | |
| year = "2023", | |
| address = "Neuchatel, Switzerland", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2023.swisstext-1.6", | |
| pages = "54--69", | |
| } | |
| ``` |