Triple

T11389512
Position Surface form Disambiguated ID Type / Status
Subject Vanderbilt University School of Medicine E269796 entity
Predicate hasDivision P35 FINISHED
Object Department of Biomedical Informatics
The Department of Biomedical Informatics is an academic unit specializing in the research and education of computational and data-driven methods to advance biomedical science and healthcare.
E441458 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Department of Biomedical Informatics | Statement: [Vanderbilt University School of Medicine, hasDivision, Department of Biomedical Informatics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Biomedical Informatics
Context triple: [Vanderbilt University School of Medicine, hasDivision, Department of Biomedical Informatics]
  • A. Department of Biomedical Informatics
    The Department of Biomedical Informatics is an academic division specializing in the application of information science, data analysis, and computational methods to biomedical and clinical research within Osaka University's Graduate School of Medicine.
  • B. Department of Medical Informatics
    The Department of Medical Informatics is an academic division at Kobe University's Graduate School of Medicine that focuses on the research and education of information technologies and data management in healthcare and medical science.
  • C. Department of Medical Informatics
    The Department of Medical Informatics is an academic unit at the University of Tokyo’s Faculty of Medicine that focuses on the research and education of information technologies and data science in healthcare and medical practice.
  • D. Department of Medical Informatics
    The Department of Medical Informatics is an academic unit at Tohoku University's Faculty of Medicine that focuses on the application of information science and technology to healthcare, clinical practice, and biomedical research.
  • E. Department of Computational Biology and Medical Sciences
    The Department of Computational Biology and Medical Sciences is an academic unit specializing in the integration of computational methods with biological and medical research to advance understanding of complex life and health systems.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Department of Biomedical Informatics
Triple: [Vanderbilt University School of Medicine, hasDivision, Department of Biomedical Informatics]
Generated description
The Department of Biomedical Informatics is an academic unit specializing in the research and education of computational and data-driven methods to advance biomedical science and healthcare.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Biomedical Informatics
Target entity description: The Department of Biomedical Informatics is an academic unit specializing in the research and education of computational and data-driven methods to advance biomedical science and healthcare.
  • A. Department of Biomedical Informatics chosen
    The Department of Biomedical Informatics is an academic division specializing in the application of information science, data analysis, and computational methods to biomedical and clinical research within Osaka University's Graduate School of Medicine.
  • B. Department of Medical Informatics
    The Department of Medical Informatics is an academic division at Kobe University's Graduate School of Medicine that focuses on the research and education of information technologies and data management in healthcare and medical science.
  • C. Department of Medical Informatics
    The Department of Medical Informatics is an academic unit at the University of Tokyo’s Faculty of Medicine that focuses on the research and education of information technologies and data science in healthcare and medical practice.
  • D. Department of Medical Informatics
    The Department of Medical Informatics is an academic unit at Tohoku University's Faculty of Medicine that focuses on the application of information science and technology to healthcare, clinical practice, and biomedical research.
  • E. Department of Computational Biology and Medical Sciences
    The Department of Computational Biology and Medical Sciences is an academic unit specializing in the integration of computational methods with biological and medical research to advance understanding of complex life and health systems.
  • F. None of above.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7fc389d4c81909515a5c8b0099c36 completed April 9, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58c672da48190affacc0f19ef0c7a completed April 20, 2026, 2:16 a.m.
NEDg Description generation batch_69e59774e6648190a38b2515a83c2e0c completed April 20, 2026, 3:03 a.m.
NED2 Entity disambiguation (via description) batch_69e5a3abf24481908fb71f4ef6b13532 completed April 20, 2026, 3:55 a.m.
Created at: April 8, 2026, 9:34 p.m.