> LASIGE: Annotating a multilingual COVID-19-related corpus for BLAH7
LASIGE: Annotating a multilingual COVID-19-related corpus for BLAH7
The global motivation is the creation of parallel multilingual datasets for text mining systems in COVID-19-related literature. Tracking the most recent advances in the COVID-19-related research is essential given the novelty of the disease and its impact on society. Still, the pace of publication requires automatic approaches to access and organize the knowledge that keeps being produced every day. It is necessary to develop text mining pipelines to assist in that task, which is only possible with evaluation datasets. However, there is a lack of COVID-19-related datasets, even more, if considering other languages besides English. The expected contribution of the project will be the annotation of a multilingual parallel dataset (EN-PT), providing this resource to the community to improve the text mining research on COVID-19-related literature.
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Annotations in COVID-19 related PubMed abstracts from the following ontologies: Disease Ontology ("do"), Gene Ontology ("go"), Human Phenotype Ontology ("hpo"), ChEBI ontology ("chebi"), MeSH
Entities and relations annotations from the following ontologies: Disease Ontology ('DO'), Gene Ontology ('GO'), Human Phenotype Ontology ('HPO'), and ChEBI ontology ('CHEBI').
Annotations in Portuguese COVID-19 related abstracts from MeSH terminology
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