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Description
The dataset contains a subset of texts from Elgold intermediate: raw texts with named entities marked and linked to corresponding Wikipedia articles. The texts were annotated by 31 participants during the 1.5-hour session.
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
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
File details
- License:
-
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CC BYAttribution
Details
- Year of publication:
- 2024
- Verification date:
- 2024-07-30
- Dataset language:
- English
- Fields of science:
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- information and communication technology (Engineering and Technology)
- DOI:
- DOI ID 10.34808/th9p-e861 open in new tab
- Series:
- Verified by:
- Gdańsk University of Technology
Keywords
References
- dataset Elgold: gold standard, multi-genre dataset for named entity recognition and linking
- dataset Elgold intermediate: raw texts
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