Triple

T360597
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Medicine and Health Sciences (McGill University) E7841 entity
Predicate hasUnit P35 FINISHED
Object 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.
E45743 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, Biostatistics and Occupational Health | Statement: [Faculty of Medicine and Health Sciences (McGill University), hasUnit, Department of Epidemiology, Biostatistics and Occupational Health]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology, Biostatistics and Occupational Health
Context triple: [Faculty of Medicine and Health Sciences (McGill University), hasUnit, Department of Epidemiology, Biostatistics and Occupational Health]
  • A. Department of Biostatistics
    The Department of Biostatistics at the Harvard T.H. Chan School of Public Health is a leading academic center for developing and applying statistical methods to advance biomedical, public health, and quantitative science research.
  • B. Department of Health Policy and Management
    The Department of Health Policy and Management is an academic unit at the Harvard T.H. Chan School of Public Health focused on research and education in health policy, health systems, and healthcare management.
  • C. Department of Global Health and Population
    The Department of Global Health and Population is an academic department at the Harvard T.H. Chan School of Public Health focused on research, education, and policy to improve health and reduce inequalities worldwide.
  • D. School of Public Health
    The School of Public Health at the University of California, Berkeley is a leading institution dedicated to research, education, and practice in public health disciplines such as epidemiology, environmental health, health policy, and global health.
  • E. Division of Cancer Control and Population Sciences
    The Division of Cancer Control and Population Sciences is a branch of the National Cancer Institute that leads research and programs focused on understanding cancer burden, risk factors, prevention, and outcomes at the population level.
  • 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, Biostatistics and Occupational Health
Triple: [Faculty of Medicine and Health Sciences (McGill University), hasUnit, Department of Epidemiology, Biostatistics and Occupational Health]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology, Biostatistics and Occupational Health
Target entity description: 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.
  • A. Department of Biostatistics
    The Department of Biostatistics at the Harvard T.H. Chan School of Public Health is a leading academic center for developing and applying statistical methods to advance biomedical, public health, and quantitative science research.
  • B. Department of Health Policy and Management
    The Department of Health Policy and Management is an academic unit at the Harvard T.H. Chan School of Public Health focused on research and education in health policy, health systems, and healthcare management.
  • C. Department of Global Health and Population
    The Department of Global Health and Population is an academic department at the Harvard T.H. Chan School of Public Health focused on research, education, and policy to improve health and reduce inequalities worldwide.
  • D. School of Public Health
    The School of Public Health at the University of California, Berkeley is a leading institution dedicated to research, education, and practice in public health disciplines such as epidemiology, environmental health, health policy, and global health.
  • E. Division of Cancer Control and Population Sciences
    The Division of Cancer Control and Population Sciences is a branch of the National Cancer Institute that leads research and programs focused on understanding cancer burden, risk factors, prevention, and outcomes at the population level.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebccb8d88190a31f7c443a0c8566 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e57a56e081909004fcd7e15f457c completed March 1, 2026, 7:06 a.m.
NEDg Description generation batch_69a3e5e50b848190ab5d036719048df8 completed March 1, 2026, 7:08 a.m.
NED2 Entity disambiguation (via description) batch_69a3e63c749c8190b5bfd85b7ccafa9c completed March 1, 2026, 7:09 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.