Triple

T10073921
Position Surface form Disambiguated ID Type / Status
Subject University of Iowa College of Public Health E213699 entity
Predicate hasDepartment P35 FINISHED
Object Department of Epidemiology
The Department of Epidemiology is an academic unit focused on studying the patterns, causes, and prevention of disease in populations through research, education, and public health practice.
E838300 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 Epidemiology | Statement: [University of Iowa College of Public Health, hasDepartment, Department of Epidemiology]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology
Context triple: [University of Iowa College of Public Health, hasDepartment, Department of Epidemiology]
  • A. Department of Epidemiology and Biostatistics
    The Department of Epidemiology and Biostatistics is an academic unit specializing in the study of disease patterns, health determinants, and the statistical methods used to analyze public health and medical data.
  • B. Department of Epidemiology, Harvard T.H. Chan School of Public Health
    The Department of Epidemiology at the Harvard T.H. Chan School of Public Health is a leading academic and research department focused on studying the distribution, determinants, and prevention of disease in populations worldwide.
  • C. Department of Population Health
    The Department of Population Health is an academic and research unit at NYU Grossman School of Medicine focused on studying and improving health outcomes at the community and population levels through epidemiology, health policy, and related disciplines.
  • D. Department of Epidemiology, Biostatistics and Occupational Health
    The Department of Epidemiology, Biostatistics and Occupational Health is an academic unit at McGill University specializing in research and graduate education on population health, statistical methods, and workplace health risks.
  • E. Department of Public Health Sciences
    The Department of Public Health Sciences is an academic unit focused on research and education in population health, epidemiology, and health policy within the School of Medicine and Dentistry.
  • 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 Epidemiology
Triple: [University of Iowa College of Public Health, hasDepartment, Department of Epidemiology]
Generated description
The Department of Epidemiology is an academic unit focused on studying the patterns, causes, and prevention of disease in populations through research, education, and public health practice.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology
Target entity description: The Department of Epidemiology is an academic unit focused on studying the patterns, causes, and prevention of disease in populations through research, education, and public health practice.
  • A. Department of Epidemiology and Biostatistics
    The Department of Epidemiology and Biostatistics is an academic unit specializing in the study of disease patterns, health determinants, and the statistical methods used to analyze public health and medical data.
  • B. Department of Epidemiology, Harvard T.H. Chan School of Public Health
    The Department of Epidemiology at the Harvard T.H. Chan School of Public Health is a leading academic and research department focused on studying the distribution, determinants, and prevention of disease in populations worldwide.
  • C. Department of Population Health
    The Department of Population Health is an academic and research unit at NYU Grossman School of Medicine focused on studying and improving health outcomes at the community and population levels through epidemiology, health policy, and related disciplines.
  • D. Department of Epidemiology, Biostatistics and Occupational Health
    The Department of Epidemiology, Biostatistics and Occupational Health is an academic unit at McGill University specializing in research and graduate education on population health, statistical methods, and workplace health risks.
  • E. Department of Public Health Sciences
    The Department of Public Health Sciences is an academic unit focused on research and education in population health, epidemiology, and health policy within the School of Medicine and Dentistry.
  • F. None of above. chosen

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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd015ad488190aee3a2bfb58fb855 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29abcb72c81908c265f057532ccb7 completed April 5, 2026, 5:24 p.m.
NEDg Description generation batch_69d29b9910448190b148841c85f73501 completed April 5, 2026, 5:27 p.m.
NED2 Entity disambiguation (via description) batch_69d29c285090819093e1a584c1ae9556 completed April 5, 2026, 5:30 p.m.
Created at: March 30, 2026, 8:59 p.m.