This is the version 3 of the CT-EBM-SP corpus of 1200 clinical trials (292173 tokens), annotated with 23 entity types and 18 relation types, covering Unified Medical Language System (UMLS) semantic groups, drug-related information, temporal data, and negation/speculation. It includes 11 encoded attributes (e.g., event temporality and experiencer status) and normalized entities to UMLS Concept Unique Identifiers. The corpus contains 87037 entities, including nested and discontinuous entities, 16597 attributes and 68206 relationships. Inter-annotator agreement (IAA) achieved average F1 values of 0.861 (entities), 0.810 (attributes), and 0.791 (relations). 81.75% of entities were normalized (IAA: F1 = 0.966). The repository includes the code to benchmark this dataset by fine-tuning Transformer models for relation extraction and medical concept normalization. In the relation extraction task, the average F1 ranged from 0.858 to 0.879. In the medical concept normalization task, the accuracy at rank 1 was 0.896.
