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The GDA dataset is a sentence-level evaluation dataset for extracting gene‑disease associations, developed by Nourani and Reshadata (2020). Built on the DisGeNET and PubTator databases, it contains 8,000 sentences covering 1,904 diseases and 3,635 genes. The dataset is split into training, validation, and test sets, each instance providing multiple fields such as gene ID, disease name, association type, etc. Construction involved extracting relevant sentences from PubMed abstracts and applying systematic filtering to ensure high‑quality negative samples.
