Извлечение Биомедицинских Отношений
Related Papers
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction
AbstractRecently, kernelized locality sensitive hashcodes have been successfully employed as representations of natural language text, especially showing high relevance to biomedical relation extraction tasks. In this paper, we propose to …...
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes
AbstractWe introduce ChemDisGene, a new dataset for training and evaluating multi-class multi-label biomedical relation extraction models. Our dataset contains 80k biomedical research abstracts labeled with mentions of chemicals, diseases, and …...
Decorate the Examples: A Simple Method of Prompt Design for Biomedical Relation Extraction
AbstractRelation extraction is a core problem for natural language processing in the biomedical domain. Recent research on relation extraction showed that prompt-based learning improves the performance on both fine-tuning on …...
Document-level Biomedical Relation Extraction Based on Multi-Dimensional Fusion Information and Multi-Granularity Logical Reasoning
AbstractDocument-level biomedical relation extraction (Bio-DocuRE) is an important branch of biomedical text mining that aims to automatically extract all relation facts from the biomedical text. Since there are a considerable …...
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?
AbstractTwo key obstacles in biomedical relation extraction (RE) are the scarcity of annotations and the prevalence of instances without explicitly pre-defined labels due to low annotation coverage. Existing approaches, which …...