Hugging Face's logo

Datasets:
adithya7
/
xlel_wd

Languages:
Afrikaans
Arabic
Belarusian
Multilinguality:
multilingual
Size Categories:
1M<n<10M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
ArXiv:
Tags:
License:
Dataset card Viewer Files Community
1
xlel_wd / README.md
adithya7's picture
adithya7
Update README.md
a6d542d
preview code
|
raw history blame contribute delete
No virus
7.96 kB
metadata
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

Dataset Description

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.