BiomedicalDatasets
material
ID: biomedicaldatasets
Related Papers
Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs
AbstractDocument-level relation extraction is a complex human process that requires logical inference to extract relationships between named entities in text. Existing approaches use graph-based neural models with words as nodes …...
Relation Extraction using Explicit Context Conditioning
AbstractRelation extraction (RE) aims to label relations between groups of marked entities in raw text. Most current RE models learn context-aware representations of the target entities that are then used …...
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios
AbstractDomain adaptation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as bioNER, domain adaptation methods often suffer from the challenging linguistic …...