Datasets for Out-of-KB Mention Discovery with Entity Linking
- 1. University of Oxford
- 2. University of Manchester & University of Oxford
- 3. Nankai University
Description
The repository contains datasets for out-of-KB mention discovery from texts, documented in the work, Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking, on arXiv: https://arxiv.org/abs/2302.07189 (CIKM 2023).
Each data setting (as a sub-folder) contains train, valid, and test files and also 100 random sample files for each data split for debugging.
Data folder names with “syn_full” at the end are synonym augmented data (each synonym as an entity) for the setting.
Ontology .jsonl files have two versions for each, "syn_attr" setting treats synonyms are attributes, "syn_full" setting treats synonyms as entities.
Data scripts are available at https://github.com/KRR-Oxford/BLINKout#data-scripts
Acknowledgement of the data sources below:
ShARe/CLEF 2013 dataset is from https://physionet.org/content/shareclefehealth2013/1.0/
MedMention dataset is from https://github.com/chanzuckerberg/MedMentions
UMLS (versions 2012AB, 2014AB, 2017AA) is from https://www.nlm.nih.gov/research/umls/index.html
SNOMED CT (corresponding versions) is from https://www.nlm.nih.gov/healthit/snomedct/index.html
NILK dataset is from https://zenodo.org/record/6607514
WikiData 2017 dump is from https://archive.org/download/enwiki-20170220/enwiki-20170220-pages-articles.xml.bz2
Files
Out-of-KB datasets 9 Aug 2023 version.zip
Files
(113.4 MB)
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