Triple

T8025876
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Life Sciences & Medicine E186851 entity
Predicate hasUnit P35 FINISHED
Object School of Life Course & Population Sciences
The School of Life Course & Population Sciences is an academic unit focused on understanding health and disease across the lifespan and within populations, typically through interdisciplinary research and teaching in epidemiology, public health, and related fields.
E590680 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: School of Life Course & Population Sciences | Statement: [Faculty of Life Sciences & Medicine, hasUnit, School of Life Course & Population Sciences]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: School of Life Course & Population Sciences
Context triple: [Faculty of Life Sciences & Medicine, hasUnit, School of Life Course & Population Sciences]
  • A. Institute of Population and Public Health
    The Institute of Population and Public Health is a Canadian research body that supports and advances research on population health, public health policy, and health equity across communities.
  • B. School of Population and Public Health
    The School of Population and Public Health is an academic unit specializing in research and education on public health, epidemiology, and population health sciences.
  • 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. School of Public Health
    The University of Michigan School of Public Health is a leading institution dedicated to research, education, and practice in public health disciplines such as epidemiology, health management, and environmental health.
  • E. School of Public Health
    The School of Public Health at Boston University is a graduate-level institution focused on research, education, and practice in public health disciplines such as epidemiology, biostatistics, health policy, and global health.
  • 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: School of Life Course & Population Sciences
Triple: [Faculty of Life Sciences & Medicine, hasUnit, School of Life Course & Population Sciences]
Generated description
The School of Life Course & Population Sciences is an academic unit focused on understanding health and disease across the lifespan and within populations, typically through interdisciplinary research and teaching in epidemiology, public health, and related fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: School of Life Course & Population Sciences
Target entity description: The School of Life Course & Population Sciences is an academic unit focused on understanding health and disease across the lifespan and within populations, typically through interdisciplinary research and teaching in epidemiology, public health, and related fields.
  • A. Institute of Population and Public Health
    The Institute of Population and Public Health is a Canadian research body that supports and advances research on population health, public health policy, and health equity across communities.
  • B. School of Population and Public Health chosen
    The School of Population and Public Health is an academic unit specializing in research and education on public health, epidemiology, and population health sciences.
  • 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. School of Public Health
    The University of Michigan School of Public Health is a leading institution dedicated to research, education, and practice in public health disciplines such as epidemiology, health management, and environmental health.
  • E. School of Public Health
    The School of Public Health at Boston University is a graduate-level institution focused on research, education, and practice in public health disciplines such as epidemiology, biostatistics, health policy, and global health.
  • 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_69ca82ad4e2c8190a693e3c9e30fe66f completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ec9983c8190b468c13f5b5beb63 completed March 31, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56da597c8190931091482d60b0a6 completed March 31, 2026, 11:20 p.m.
NEDg Description generation batch_69cc58aac4288190a2be4691fc740171 completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cbf8278819085ff32a0494d544e completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:21 p.m.