annotations_creators:
- found
language_creators:
- found
language:
- af
- ar
- be
- bg
- bn
- ca
- cs
- da
- de
- el
- en
- es
- fa
- fi
- fr
- he
- hi
- hu
- id
- it
- ja
- ko
- ml
- mr
- ms
- nl
- 'no'
- pl
- pt
- ro
- ru
- si
- sk
- sl
- sr
- sv
- sw
- ta
- te
- th
- tr
- uk
- vi
- zh
license:
- cc-by-4.0
multilinguality:
- multilingual
pretty_name: >-
XLEL-WD is a multilingual event linking dataset. This dataset contains mention
references in multilingual Wikipedia/Wikinews articles to event items from
Wikidata. The descriptions for Wikidata event items are taken from the
corresponding Wikipedia articles.
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories: []
task_ids: []
Dataset Card for XLEL-WD
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/adithya7/xlel-wd
- Repository: https://github.com/adithya7/xlel-wd
- Paper: https://arxiv.org/abs/2204.06535
- Leaderboard: N/A
- Point of Contact: Adithya Pratapa
Dataset Summary
XLEL-WD is a multilingual event linking dataset. This dataset repo contains mention references in multilingual Wikipedia/Wikinews articles to event items from Wikidata.
The descriptions for Wikidata event items were collected from the corresponding Wikipedia articles. Download the event dictionary from adithya7/xlel_wd_dictionary.
Supported Tasks and Leaderboards
This dataset can be used for the task of event linking. There are two variants of the task, multilingual and crosslingual.
- Multilingual linking: mention and the event descriptions are in the same language.
- Crosslingual linking: the event descriptions are only available in English.
Languages
This dataset contains text from 44 languages. The language names and their ISO 639-1 codes are listed below. For details on the dataset distribution for each language, refer to the original paper.
Language | Code | Language | Code | Language | Code | Language | Code |
---|---|---|---|---|---|---|---|
Afrikaans | af | Arabic | ar | Belarusian | be | Bulgarian | bg |
Bengali | bn | Catalan | ca | Czech | cs | Danish | da |
German | de | Greek | el | English | en | Spanish | es |
Persian | fa | Finnish | fi | French | fr | Hebrew | he |
Hindi | hi | Hungarian | hu | Indonesian | id | Italian | it |
Japanese | ja | Korean | ko | Malayalam | ml | Marathi | mr |
Malay | ms | Dutch | nl | Norwegian | no | Polish | pl |
Portuguese | pt | Romanian | ro | Russian | ru | Sinhala | si |
Slovak | sk | Slovene | sl | Serbian | sr | Swedish | sv |
Swahili | sw | Tamil | ta | Telugu | te | Thai | th |
Turkish | tr | Ukrainian | uk | Vietnamese | vi | Chinese | zh |
Dataset Structure
Data Instances
Each instance in the train.jsonl
, dev.jsonl
and test.jsonl
files follow the below template.
{
"context_left": "Minibaev's first major international medal came in the men's synchronized 10 metre platform event at the ",
"mention": "2010 European Championships",
"context_right": ".",
"context_lang": "en",
"label_id": "830917",
}
Data Fields
Field | Meaning |
---|---|
mention |
text span of the mention |
context_left |
left paragraph context from the document |
context_right |
right paragraph context from the document |
context_lang |
language of the context (and mention) |
context_title |
document title of the mention (only Wikinews subset) |
context_date |
document publication date of the mention (only Wikinews subset) |
label_id |
Wikidata label ID for the event. E.g. 830917 refers to Q830917 from Wikidata. |
Data Splits
The Wikipedia-based corpus has three splits. This is a zero-shot evaluation setup.
Train | Dev | Test | Total | |
---|---|---|---|---|
Events | 8653 | 1090 | 1204 | 10947 |
Event Sequences | 6758 | 844 | 846 | 8448 |
Mentions | 1.44M | 165K | 190K | 1.8M |
Languages | 44 | 44 | 44 | 44 |
The Wikinews-based evaluation set has two variants, one for cross-domain evaluation and another for zero-shot evaluation.
(Cross-domain) Test | (Zero-shot) Test | |
---|---|---|
Events | 802 | 149 |
Mentions | 2562 | 437 |
Languages | 27 | 21 |
Dataset Creation
Curation Rationale
This dataset helps address the task of event linking. KB linking is extensively studied for entities, but its unclear if the same methodologies can be extended for linking mentions to events from KB. We use Wikidata as our KB, as it allows for linking mentions from multilingual Wikipedia and Wikinews articles.
Source Data
Initial Data Collection and Normalization
First, we utilize spatial & temporal properties from Wikidata to identify event items. Second, we identify corresponding multilingual Wikipedia pages for each Wikidata event item. Third, we pool hyperlinks from multilingual Wikipedia & Wikinews articles to these event items.
Who are the source language producers?
The documents in XLEL-WD are written by Wikipedia and Wikinews contributors in respective languages.
Annotations
Annotation process
This dataset was originally collected automatically from Wikipedia, Wikinews and Wikidata. It was post-processed to improve data quality.
Who are the annotators?
The annotations in XLEL-WD (hyperlinks from Wikipedia/Wikinews to Wikidata) are added the original Wiki contributors.
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
XLEL-WD v1.0.0 mostly caters to eventive nouns from Wikidata. It does not include any links to other event items from Wikidata such as disease outbreak (Q3241045), military offensive (Q2001676) and war (Q198).
Additional Information
Dataset Curators
The dataset was curated by Adithya Pratapa, Rishubh Gupta and Teruko Mitamura. The code for collecting the dataset is available at Github:xlel-wd.
Licensing Information
XLEL-WD dataset is released under CC-BY-4.0 license.
Citation Information
@article{pratapa-etal-2022-multilingual,
title = {Multilingual Event Linking to Wikidata},
author = {Pratapa, Adithya and Gupta, Rishubh and Mitamura, Teruko},
publisher = {arXiv},
year = {2022},
url = {https://arxiv.org/abs/2204.06535},
}
Contributions
Thanks to @adithya7 for adding this dataset.