Datasets:
wikidata_id stringlengths 3 10 | lastrevid int64 306M 1.56B | label stringlengths 1 120 |
|---|---|---|
Q110425075 | 1,556,708,450 | Lopata |
Q109946856 | 1,556,662,944 | Leschallier |
Q110409516 | 1,556,627,503 | Johann-Heinrich |
Q108868778 | 1,556,622,179 | Korndรถrfer |
Q109411983 | 1,556,588,123 | Padrรณ |
Q101214825 | 1,556,587,003 | Akofa |
Q106335056 | 1,556,559,942 | Zemmel |
Q110419747 | 1,556,542,153 | Rickwart |
Q110419795 | 1,556,536,253 | Lapeyra |
Q109942293 | 1,556,534,964 | Preisigke |
Q106113565 | 1,556,529,368 | Rixovรก |
Q96722160 | 1,556,526,608 | Ri |
Q110417577 | 1,556,511,658 | Rรผttinger |
Q110419264 | 1,556,511,403 | Haldimand |
Q110419020 | 1,556,511,391 | Bolau |
Q110418692 | 1,556,511,340 | Brodyaga |
Q110418324 | 1,556,511,259 | Mรกriรกssy |
Q110418136 | 1,556,511,230 | Fonssagrives |
Q110418126 | 1,556,511,213 | van de Vijver |
Q110418025 | 1,556,511,112 | Paufler |
Q110417998 | 1,556,511,102 | Zuijderwijk |
Q110417588 | 1,556,511,091 | Haguenin |
Q110417455 | 1,556,509,939 | Budinszky |
Q110416022 | 1,556,509,922 | Pongolini |
Q110415825 | 1,556,509,906 | Schipa |
Q110415699 | 1,556,509,890 | Imbruglia |
Q110414976 | 1,556,509,872 | Lo Muzio |
Q110414968 | 1,556,509,787 | Rokx |
Q110414876 | 1,556,509,775 | Socrate |
Q110414777 | 1,556,509,765 | Tonies |
Q110414767 | 1,556,509,746 | Geurts van Kessel |
Q110414469 | 1,556,509,646 | Speksnijder |
Q110414412 | 1,556,509,611 | van Lokhorst |
Q110414387 | 1,556,509,506 | Schryff |
Q110414369 | 1,556,509,488 | Roobol |
Q110414347 | 1,556,509,479 | Witvliet |
Q110414321 | 1,556,509,463 | Ter Laan |
Q110414288 | 1,556,509,342 | Van Den Ende |
Q110360226 | 1,556,509,326 | van den Ende |
Q110414277 | 1,556,509,249 | van der Ende |
Q110414256 | 1,556,508,977 | Van den Ende |
Q110414006 | 1,556,508,740 | Filomusi-Guelfi |
Q110413453 | 1,556,508,726 | Virieux |
Q110412457 | 1,556,508,711 | Mazanowski |
Q110411993 | 1,556,508,606 | Alzari |
Q110411981 | 1,556,508,500 | von Schrรถderร |
Q110411789 | 1,556,507,410 | Rockx |
Q110411555 | 1,556,507,087 | van Nierop |
Q110410957 | 1,556,507,047 | Allwork |
Q110409748 | 1,556,507,025 | Sinistrero |
Q110409560 | 1,556,506,920 | Gropelli |
Q110409425 | 1,556,506,839 | Kalniลa |
Q110409304 | 1,556,506,784 | Marylski |
Q110408983 | 1,556,506,666 | Bฤrziลa |
Q110408656 | 1,556,506,582 | Vialardi |
Q110408258 | 1,556,506,464 | Olorรณn |
Q110408099 | 1,556,506,250 | Ollo |
Q110412203 | 1,556,504,098 | Stoevesandt |
Q110419005 | 1,556,503,968 | Stรถvesand |
Q101043160 | 1,556,503,837 | Stรถwsand |
Q100587794 | 1,556,501,368 | Stuyvesant |
Q95852982 | 1,556,495,915 | Christian Stรถvesand |
Q110418823 | 1,556,484,715 | von Opel |
Q105955911 | 1,556,481,907 | Marie |
Q106307292 | 1,556,459,013 | Ringvatnet |
Q83338292 | 1,556,450,484 | Abelen |
Q83338286 | 1,556,450,362 | Abbel |
Q83338298 | 1,556,444,403 | Abelius |
Q109940969 | 1,556,436,850 | Mvondo |
Q109940779 | 1,556,436,737 | Mbaka |
Q97097207 | 1,556,399,212 | Telegdi |
Q89974784 | 1,556,368,257 | Scherphuis |
Q110418284 | 1,556,363,767 | Obbo |
Q104002197 | 1,556,344,354 | Van van de Vijver |
Q83374934 | 1,556,336,341 | Oppler |
Q83374933 | 1,556,327,443 | Oppl |
Q96600611 | 1,556,317,560 | Gerhard von Glahn |
Q83374622 | 1,556,301,101 | Obelt |
Q109937640 | 1,556,298,323 | Ponjoan |
Q110393330 | 1,556,293,609 | Rips |
Q110413372 | 1,556,237,147 | Opelt-Stoevesandt |
Q107423630 | 1,556,201,633 | Robert Pfleger |
Q96582228 | 1,556,181,126 | Flahault |
Q107203945 | 1,556,176,775 | Abdulfatai Yahaya Seriki |
Q109935462 | 1,556,173,700 | Creuzet |
Q79392884 | 1,556,165,966 | Georgievna |
Q109935312 | 1,556,164,751 | ฤฐsmayฤฑlov |
Q109934255 | 1,556,132,312 | Poincignon |
Q110381224 | 1,556,130,039 | ter Laan |
Q110414079 | 1,556,118,604 | Costenco |
Q110414104 | 1,556,118,414 | Kostenko |
Q110413768 | 1,556,116,777 | Odbald |
Q110386877 | 1,556,095,476 | Wรถlbling |
Q110334596 | 1,556,093,883 | Huldermann |
Q106832845 | 1,556,076,975 | Hans Joachim Stoevesandt |
Q109932031 | 1,556,049,005 | Ferrerons |
Q104621420 | 1,556,021,706 | Sigismonda |
Q63217071 | 1,555,994,396 | Johan Erik |
Q63689481 | 1,555,993,901 | Joan Enric |
Q110409460 | 1,555,989,548 | Kenwrick |
YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Wikidata Labels
Large parallel corpus for machine translation
- Entity label data extracted from Wikidata (2022-01-03), filtered for item entities only
- Only download the languages you need with
datasets>=2.14.0 - Similar dataset: https://huggingface.co/datasets/wmt/wikititles (18 Wikipedia titles pairs instead of all Wikidata entities)
Dataset Details
Dataset Sources
- Wikidata JSON dump (wikidata-20220103-all.json.gz) https://www.wikidata.org/wiki/Wikidata:Database_download
Uses
You can generate parallel text examples from this dataset like below:
from datasets import load_dataset
import pandas as pd
def parallel_labels(lang_codes: list, how="inner", repo_id="rayliuca/wikidata_entity_label", merge_config={}, datasets_config={}) -> pd.DataFrame:
out_df = None
for lc in lang_codes:
dataset = load_dataset(repo_id, lc, **datasets_config)
dataset_df = dataset['label'].to_pandas().rename(columns={"label":lc}).drop(columns=['lastrevid'])
if out_df is None:
out_df = dataset_df
else:
out_df = out_df.merge(
dataset_df,
on='wikidata_id',
how=how,
**merge_config
)
return out_df
# Note: the "en" subset is >4GB
parallel_labels(['en', 'fr', 'ja', 'zh']).head()
Output
| wikidata_id | en | fr | ja | zh | |
|---|---|---|---|---|---|
| 0 | Q109739412 | SARS-CoV-2 Omicron variant | variant Omicron du SARS-CoV-2 | SARSใณใญใใฆใคใซใน2-ใชใใฏใญใณๆ ช | ๅด้ๆฅๆงๅผๅธ้็ๅ็พคๅ ็็ ๆฏ2ๅOmicron่ฎ็ฐๆ ช |
| 1 | Q108460606 | Ulughbegsaurus | Ulughbegsaurus | ใฆใซใฐใใฐใตใฆใซใน | ๅ ้ญฏไผฏ้พๅฑฌ |
| 2 | Q108556886 | AUKUS | AUKUS | AUKUS | AUKUS |
| 3 | Q106496152 | Claude Joseph | Claude Joseph | ใฏใญใผใใปใธใงใผใ | ๅ ๆดๅพทยท็บฆ็ๅคซ |
| 4 | Q105519361 | The World's Finest Assassin Gets Reincarnated in a Different World as an Aristocrat | The World's Finest Assassin Gets Reincarnated in Another World as an Aristocrat | ไธ็ๆ้ซใฎๆๆฎบ่ ใ็ฐไธ็่ฒดๆใซ่ปข็ใใ | ไธ็้ ๅฐ็ๆๆฎบ่ ่ฝ็็บ็ฐไธ็่ฒดๆ |
Note: this example table above shows a quirk(?) of the Wiki data. The French Wikipedia page The World's Finest Assassin Gets Reincarnated in Another World as an Aristocrat uses English for its title. While this could be disadvantageous for direct translation training, it also provides insights into how native speakers might call this entity instead of the literal translation on the Wiki page as well
Dataset Structure
Each language has its own subset (aka config), which means you only have to download the languages you need with datasets>=2.14.0
Each subset has these fields:
- wikidata_id
- lastrevid
- label
Dataset Creation
Data Collection and Processing
- Filtered for item entities only
- Ignored the descriptions as those texts are not very parallel
Bias, Risks, and Limitations
- Might be slightly outdated (2022)
- Popular languages have more entries
- Labels are not guaranteed to be literal translations (see examples above)
- Downloads last month
- 1,244