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---
license: cc-by-nc-4.0
task_categories:
- fill-mask
- text-generation
language:
- am
- ar
- ay
- bm
- bbj
- bn
- bs
- bg
- ca
- cs
- ku
- da
- el
- en
- et
- ee
- fil
- fi
- fr
- fon
- gu
- guw
- ha
- he
- hi
- hu
- ig
- id
- it
- ja
- kk
- km
- ko
- lv
- ln
- lt
- lg
- luo
- mk
- mos
- my
- nl
- 'no'
- ne
- om
- or
- pa
- pcm
- fa
- pl
- pt
- mg
- ro
- rn
- ru
- sn
- so
- es
- sr
- sq
- sw
- sv
- ta
- tet
- ti
- th
- tn
- tr
- tw
- uk
- ur
- wo
- xh
- yo
- zh
- zu
- de
multilinguality:
- multilingual
pretty_name: PolyNews
size_categories:
- 1K<n<10K
source_datasets:
- masakhanews
- mafand
- wikinews
- wmt-news
- globalvoices
tags:
- news
- polynews
- mafand
- masakhanews
- wikinews
- globalvoices
- wmtnews
configs:
- config_name: amh_Ethi
data_files:
- split: train
path: data/amh_Ethi/train.parquet.gzip
- config_name: arb_Arab
data_files:
- split: train
path: data/arb_Arab/train.parquet.gzip
- config_name: ayr_Latn
data_files:
- split: train
path: data/ayr_Latn/train.parquet.gzip
- config_name: bam_Latn
data_files:
- split: train
path: data/bam_Latn/train.parquet.gzip
- config_name: bbj_Latn
data_files:
- split: train
path: data/bbj_Latn/train.parquet.gzip
- config_name: ben_Beng
data_files:
- split: train
path: data/ben_Beng/train.parquet.gzip
- config_name: bos_Latn
data_files:
- split: train
path: data/bos_Latn/train.parquet.gzip
- config_name: bul_Cyrl
data_files:
- split: train
path: data/bul_Cyrl/train.parquet.gzip
- config_name: cat_Latn
data_files:
- split: train
path: data/cat_Latn/train.parquet.gzip
- config_name: ces_Latn
data_files:
- split: train
path: data/ces_Latn/train.parquet.gzip
- config_name: ckb_Arab
data_files:
- split: train
path: data/ckb_Arab/train.parquet.gzip
- config_name: dan_Latn
data_files:
- split: train
path: data/dan_Latn/train.parquet.gzip
- config_name: deu_Latn
data_files:
- split: train
path: data/deu_Latn/train.parquet.gzip
- config_name: ell_Grek
data_files:
- split: train
path: data/ell_Grek/train.parquet.gzip
- config_name: eng_Latn
data_files:
- split: train
path: data/eng_Latn/train.parquet.gzip
- config_name: est_Latn
data_files:
- split: train
path: data/est_Latn/train.parquet.gzip
- config_name: ewe_Latn
data_files:
- split: train
path: data/ewe_Latn/train.parquet.gzip
- config_name: fil_Latn
data_files:
- split: train
path: data/fil_Latn/train.parquet.gzip
- config_name: fin_Latn
data_files:
- split: train
path: data/fin_Latn/train.parquet.gzip
- config_name: fon_Latn
data_files:
- split: train
path: data/fon_Latn/train.parquet.gzip
- config_name: fra_Latn
data_files:
- split: train
path: data/fra_Latn/train.parquet.gzip
- config_name: guj_Gujr
data_files:
- split: train
path: data/guj_Gujr/train.parquet.gzip
- config_name: guw_Latn
data_files:
- split: train
path: data/guw_Latn/train.parquet.gzip
- config_name: hau_Latn
data_files:
- split: train
path: data/hau_Latn/train.parquet.gzip
- config_name: heb_Hebr
data_files:
- split: train
path: data/heb_Hebr/train.parquet.gzip
- config_name: hin_Deva
data_files:
- split: train
path: data/hin_Deva/train.parquet.gzip
- config_name: hun_Latn
data_files:
- split: train
path: data/hun_Latn/train.parquet.gzip
- config_name: ibo_Latn
data_files:
- split: train
path: data/ibo_Latn/train.parquet.gzip
- config_name: ind_Latn
data_files:
- split: train
path: data/ind_Latn/train.parquet.gzip
- config_name: ita_Latn
data_files:
- split: train
path: data/ita_Latn/train.parquet.gzip
- config_name: jpn_Jpan
data_files:
- split: train
path: data/jpn_Jpan/train.parquet.gzip
- config_name: kaz_Cyrl
data_files:
- split: train
path: data/kaz_Cyrl/train.parquet.gzip
- config_name: khm_Khmr
data_files:
- split: train
path: data/khm_Khmr/train.parquet.gzip
- config_name: kor_Hang
data_files:
- split: train
path: data/kor_Hang/train.parquet.gzip
- config_name: lav_Latn
data_files:
- split: train
path: data/lav_Latn/train.parquet.gzip
- config_name: lin_Latn
data_files:
- split: train
path: data/lin_Latn/train.parquet.gzip
- config_name: lit_Latn
data_files:
- split: train
path: data/lit_Latn/train.parquet.gzip
- config_name: lug_Latn
data_files:
- split: train
path: data/lug_Latn/train.parquet.gzip
- config_name: luo_Latn
data_files:
- split: train
path: data/luo_Latn/train.parquet.gzip
- config_name: mkd_Cyrl
data_files:
- split: train
path: data/mkd_Cyrl/train.parquet.gzip
- config_name: mos_Latn
data_files:
- split: train
path: data/mos_Latn/train.parquet.gzip
- config_name: mya_Mymr
data_files:
- split: train
path: data/mya_Mymr/train.parquet.gzip
- config_name: nld_Latn
data_files:
- split: train
path: data/nld_Latn/train.parquet.gzip
- config_name: nor_Latn
data_files:
- split: train
path: data/nor_Latn/train.parquet.gzip
- config_name: npi_Deva
data_files:
- split: train
path: data/npi_Deva/train.parquet.gzip
- config_name: orm_Latn
data_files:
- split: train
path: data/orm_Latn/train.parquet.gzip
- config_name: ory_Orya
data_files:
- split: train
path: data/ory_Orya/train.parquet.gzip
- config_name: pan_Guru
data_files:
- split: train
path: data/pan_Guru/train.parquet.gzip
- config_name: pcm_Latn
data_files:
- split: train
path: data/pcm_Latn/train.parquet.gzip
- config_name: pes_Arab
data_files:
- split: train
path: data/pes_Arab/train.parquet.gzip
- config_name: plt_Latn
data_files:
- split: train
path: data/plt_Latn/train.parquet.gzip
- config_name: pol_Latn
data_files:
- split: train
path: data/pol_Latn/train.parquet.gzip
- config_name: por_Latn
data_files:
- split: train
path: data/por_Latn/train.parquet.gzip
- config_name: ron_Latn
data_files:
- split: train
path: data/ron_Latn/train.parquet.gzip
- config_name: run_Latn
data_files:
- split: train
path: data/run_Latn/train.parquet.gzip
- config_name: rus_Cyrl
data_files:
- split: train
path: data/rus_Cyrl/train.parquet.gzip
- config_name: sna_Latn
data_files:
- split: train
path: data/sna_Latn/train.parquet.gzip
- config_name: som_Latn
data_files:
- split: train
path: data/som_Latn/train.parquet.gzip
- config_name: spa_Latn
data_files:
- split: train
path: data/spa_Latn/train.parquet.gzip
- config_name: sqi_Latn
data_files:
- split: train
path: data/sqi_Latn/train.parquet.gzip
- config_name: srp_Cyrl
data_files:
- split: train
path: data/srp_Cyrl/train.parquet.gzip
- config_name: srp_Latn
data_files:
- split: train
path: data/srp_Latn/train.parquet.gzip
- config_name: swe_Latn
data_files:
- split: train
path: data/swe_Latn/train.parquet.gzip
- config_name: swh_Latn
data_files:
- split: train
path: data/swh_Latn/train.parquet.gzip
- config_name: tam_Taml
data_files:
- split: train
path: data/tam_Taml/train.parquet.gzip
- config_name: tet_Latn
data_files:
- split: train
path: data/tet_Latn/train.parquet.gzip
- config_name: tha_Thai
data_files:
- split: train
path: data/tha_Thai/train.parquet.gzip
- config_name: tir_Ethi
data_files:
- split: train
path: data/tir_Ethi/train.parquet.gzip
- config_name: tsn_Latn
data_files:
- split: train
path: data/tsn_Latn/train.parquet.gzip
- config_name: tur_Latn
data_files:
- split: train
path: data/tur_Latn/train.parquet.gzip
- config_name: twi_Latn
data_files:
- split: train
path: data/twi_Latn/train.parquet.gzip
- config_name: ukr_Cyrl
data_files:
- split: train
path: data/ukr_Cyrl/train.parquet.gzip
- config_name: urd_Arab
data_files:
- split: train
path: data/urd_Arab/train.parquet.gzip
- config_name: wol_Latn
data_files:
- split: train
path: data/wol_Latn/train.parquet.gzip
- config_name: xho_Latn
data_files:
- split: train
path: data/xho_Latn/train.parquet.gzip
- config_name: yor_Latn
data_files:
- split: train
path: data/yor_Latn/train.parquet.gzip
- config_name: zho_Hans
data_files:
- split: train
path: data/zho_Hans/train.parquet.gzip
- config_name: zho_Hant
data_files:
- split: train
path: data/zho_Hant/train.parquet.gzip
- config_name: zul_Latn
data_files:
- split: train
path: data/zul_Latn/train.parquet.gzip
---
# Dataset Card for PolyNews
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Uses](#uses)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Data Collection and Processing](#data-collection-and-processing)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://huggingface.co/datasets/aiana94/polynews
- **Repository:** https://github.com/andreeaiana/nase
- **Paper:** [News Without Borders: Domain Adaptation of Multilingual Sentence Embeddings for Cross-lingual News Recommendation](https://arxiv.org/abs/2406.12634)
- **Point of Contact:** [Andreea Iana](https://andreeaiana.github.io/)
- **License:** [CC-BY-4.0-NC](https://creativecommons.org/licenses/by-nc/4.0/)
### Dataset Summary
PolyNews is a multilingual dataset containing news titles in 77 languages and 19 scripts.
### Uses
This dataset can be used for domain adaptation of language models, language modeling or text generation.
### Languages
There are 77 languages available:
|**Code** | **Language** | **Script** |**\#Articles (K)**|
|:-----------|:---------------------------|:-------------------|:---------|
| amh\_Ethi | Amharic | Ethiopic | 0.551 |
| arb\_Arab | Modern Standard Arabic | Arabic | 10.882 |
| ayr\_Latn | Central Aymara | Latin | 12.878 |
| bam\_Latn | Bambara | Latin | 2.916 |
| bbj\_Latn | Ghomálá’ | Latin | 1.737 |
| ben\_Beng | Bengali | Bengali | 2.268 |
| bos\_Latn | Bosnian | Latin | 0.298 |
| bul\_Cyrl | Bulgarian | Cyrillic | 1.791 |
| cat\_Latn | Catalan | Latin | 30.410 |
| ces\_Latn | Czech | Latin | 58.382 |
| ckb\_Arab | Central Kurdish | Arabic | 0.014 |
| dan\_Latn | Danish | Latin | 9.456 |
| deu\_Latn | German | Latin | 145.484 |
| ell\_Grek | Greek | Greek | 50.176 |
| eng\_Latn | English | Latin | 981.430 |
| est\_Latn | Estonian | Latin | 3.942 |
| ewe\_Latn | Éwé | Latin | 2.003 |
| fil\_Latn | Filipino | Latin | 3.3132 |
| fin\_Latn | Finnish | Latin | 19.602 |
| fon\_Latn | Fon | Latin | 2.610 |
| fra\_Latn | French | Latin | 481.117 |
| guj\_Gujr | Gujarati | Gujarati | 0.690 |
| guw\_Latn | Gun | Latin | 1.068 |
| hau\_Latn | Hausa | Latin | 7.898 |
| heb\_Hebr | Hebrew | Hebrew | 0.355 |
| hin\_Deva | Hindi | Devanagari | 0.707 |
| hun\_Latn | Hungarian | Latin | 22.219 |
| ibo\_Latn | Igbo | Latin | 7.709 |
| ind\_Latn | Indonesian | Latin | 17.749 |
| ita\_Latn | Italian | Latin | 163.396 |
| jpn\_Jpan | Japanese | Japanese | 20.778 |
| kaz\_Cyrl | Kazakh | Cyrillic | 0.763 |
| khm\_Khmr | Khmer | Khmer | 0.227 |
| kor\_Hang | Korean | Hangul | 3.527 |
| lav\_Latn | Latvian | Latin | 3.971 |
| lin\_Latn | Lingala | Latin | 0.602 |
| lit\_Latn | Lithuanian | Latin | 3.948 |
| lug\_Latn | Ganda | Latin | 4.769 |
| luo\_Latn | Luo | Latin | 4.250 |
| mkd\_Cyrl | Macedonian | Cyrillic | 10.537 |
| mos\_Latn | Mossi | Latin | 2.458 |
| mya\_Mymr | Burmese | Myanmar | 0.583 |
| nld\_Latn | Dutch | Latin | 53.184 |
| nor\_Latn | Norwegian | Latin | 0.529 |
| npi\_Deva | Nepali | Devanagari | 0.220 |
| orm\_Latn | Oromo | Latin | 1.124 |
| ory\_Orya | Odia | Oriya | 0.038 |
| pan\_Guru | Eastern Panjabi | Gurmukhi | 0.336 |
| pcm\_Latn | Nigerian Pidgin | Latin | 5.742 |
| pes\_Arab | Western Persian | Arabic | 1.431 |
| plt\_Latn | Malagasy | Latin | 393.767 |
| pol\_Latn | Polish | Latin | 80.960 |
| por\_Latn | Portuguese | Latin | 156.039 |
| ron\_Latn | Romanian | Latin | 10.472 |
| run\_Latn | Rundi | Latin | 1.113 |
| rus\_Cyrl | Russian | Cyrillic | 143.283 |
| sna\_Latn | Shona | Latin | 1.128 |
| som\_Latn | Somali | Latin | 1.019 |
| spa\_Latn | Spanish | Latin | 681.121 |
| sqi\_Latn | Albanian | Latin | 7.274 |
| srp\_Cyrl | Serbian | Cyrillic | 1.056 |
| srp\_Latn | Serbian | Latin | 58.012 |
| swe\_Latn | Swedish | Latin | 12.323 |
| swh\_Latn | Swahili | Latin | 47.337 |
| tam\_Taml | Tamil | Tamil | 0.358 |
| tet\_Latn | Tetun | Latin | 0.626 |
| tha\_Thai | Thai | Thai | 0.091 |
| tir\_Ethi | Tigrinya | Ethiopic | 0.079 |
| tsn\_Latn | Tswana | Latin | 2.075 |
| tur\_Latn | Turkish | Latin | 19.793 |
| twi\_Latn | Twi | Latin | 3.012 |
| ukr\_Cyrl | Ukrainian | Cyrillic | 0.292 |
| urd\_Arab | Urdu | Arabic | 0.804 |
| wol\_Latn | Wolof | Latin | 3.344 |
| xho\_Latn | Xhosa | Latin | 0.709 |
| yor\_Latn | Yorùbá | Latin | 8.011 |
| zho\_Hans | Chinese | Han (Simplified) | 59.771 |
| zho\_Hant | Chinese | Han (Traditional) | 54.561 |
| zul\_Latn | Zulu | Latin | 3.376 |
## Dataset Structure
### Data Instances
```
>>> from datasets import load_dataset
>>> data = load_dataset('aiana94/polynews', 'ron_Latn')
# Please, specify the language code,
# A data point example is below:
{
"text": "Un public numeros. Este uimitor succesul după doar trei ediții . ",
"provenance": "globalvoices"
}
```
### Data Fields
- text (string): news text
- provenance (string) : source dataset for the news example
### Data Splits
For all languages, there is only the `train` split.
## Dataset Creation
### Curation Rationale
Multiple multilingual, human-translated, datasets containing news texts have been released in recent years.
However, these datasets are stored in different formats and various websites, and many contain numerous near duplicates.
With PolyNews, we aim to provide an easily-accessible, unified and deduplicated dataset that combines these disparate data sources.
It can be used for domain adaptation of language models, language modeling or text generation in both high-resource and low-resource languages.
### Source Data
The source data consists of five multilingual news datasets.
- [Wikinews](https://www.wikinews.org/) (latest dump available in May 2024)
- [GlobalVoices](https://opus.nlpl.eu/GlobalVoices/corpus/version/GlobalVoices) (v2018q4)
- [WMT-News](https://opus.nlpl.eu/WMT-News/corpus/version/WMT-News) (v2019)
- [MasakhaNews](https://huggingface.co/datasets/masakhane/masakhanews) (`train` split)
- [MAFAND](https://huggingface.co/datasets/masakhane/mafand) (`train` split)
#### Data Collection and Processing
We processed the data using a **working script** which covers the entire processing pipeline. It can be found [here](https://github.com/andreeaiana/nase/blob/main/scripts/construct_polynews.sh).
The data processing pipeline consists of:
1. Downloading the WMT-News and GlobalVoices News from OPUS.
2. Downloading the latest dump from WikiNews.
3. Loading the MasakhaNews and MAFAND datasets from Hugging Face Hub (only the `train` splits).
4. Concatenating, per language, all news texts from the source datasets.
5. Data cleaning (e.g., removal of exact duplicates, short texts, texts in other scripts)
6. [MinHash near-deduplication](https://github.com/bigcode-project/bigcode-dataset/blob/main/near_deduplication/minhash_deduplication.py) per language.
### Annotations
We augment the original samples with the `provenance` annotation which specifies the original data source from which a particular examples stems.
#### Personal and Sensitive Information
The data is sourced from newspaper sources and contains mentions of public figures and individuals.
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
Users should keep in mind that the dataset contains short news texts (e.g., mostly titles), which might limit the applicability of the developed systems to other domains.
## Additional Information
### Licensing Information
The dataset is released under the [CC BY-NC Attribution-NonCommercial 4.0 International license](https://creativecommons.org/licenses/by-nc/4.0/).
### Citation Infomation
**BibTeX:**
```bibtex
@misc{iana2024news,
title={News Without Borders: Domain Adaptation of Multilingual Sentence Embeddings for Cross-lingual News Recommendation},
author={Andreea Iana and Fabian David Schmidt and Goran Glavaš and Heiko Paulheim},
year={2024},
eprint={2406.12634},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2406.12634}
}
``` |