We describe a novel dataset for the automated recognition of named taxonomic and other entities relevant to the association of viruses with their hosts. We further describe some initial results using pre-trained models on the named-entity recognition (NER) task on this novel dataset. We propose that our dataset of manually annotated abstracts now offers a Gold Standard Corpus for training future NER models in the automated extraction of host-pathogen detection methods from scientific publications, and further explain how our work makes first steps towards predicting the important human health-related concept of viral spillover risk automatically from the scientific literature.
@article{arxiv.2305.13317,
title = {A Novel Dataset Towards Extracting Virus-Host Interactions},
author = {Rasha Alshawi and Atriya Sen and Nathan S. Upham and Beckett Sterner},
journal= {arXiv preprint arXiv:2305.13317},
year = {2023}
}
Comments
for associated dataset, see https://1drv.ms/u/s!AjanaqjkM2-ShN9rMT1BqrpAQRpakQ?e=TPkFgh