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Elgold intermediate: verified by the authors

Description

The dataset contains the texts from Elgold intermediate: verified by verification team additionaly verified by the dataset authors but before the final validation step with the elgold toolset.

Each marked entity in the dataset is assigned to one of the following classes:
EVENT - Named hurricanes, battles, wars, sports events, etc.
FAC - Buildings, airports, highways, bridges, etc.
GPE - Countries, cities, states
LANGUAGE - Any named language
LAW - Named documents made into laws.
LOC - Non-GPE locations, mountain ranges, bodies of water
NORP - Nationalities or religious or political groups
ORG - Companies, agencies, institutions, etc.
PERSON - People, including fictional
PRODUCT - Objects, vehicles, foods, etc. (not services)
WORK_OF_ART - Titles of books, songs, etc.
DISEASE - Names of diseases
SUBSTANCE - Natural substances
SPECIE - Species names of animals, plants, viruses, etc.

The marked entities are embedded directly in the textual files using the following syntax:

{{mention content|entity class|Wikipedia target}}

The "mention content" is a fragment of the textual file that was marked, "entity class" is the named entity class, and "Wikipedia target" is the normalized name of the English Wikipedia page describing the entity. If the entity cannot be linked sensibly to any article the target is empty but the second pipe (|) is preserved. 

The annotated texts were not later verified by the dataset authors. It makes it a good resource for analyzing different understandings of named entity recognition tasks among the annotators. 

Dataset file

verified-by-authors.zip
281.0 kB, S3 ETag 032e08d678ec83af14e12062c9d6848e-1, downloads: 0
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5
download file verified-by-authors.zip

File details

License:
Creative Commons: by 4.0 open in new tab
CC BY
Attribution

Details

Year of publication:
2024
Verification date:
2024-10-31
Dataset language:
English
Fields of science:
  • information and communication technology (Engineering and Technology)
DOI:
DOI ID 10.34808/r2mw-3y58 open in new tab
Series:
Verified by:
Gdańsk University of Technology

Keywords

References

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