Datasets:
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:
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" (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
@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",
}