Triple

T5683507
Position Surface form Disambiguated ID Type / Status
Subject NYU Grossman School of Medicine E125252 entity
Predicate hasDepartment P35 FINISHED
Object 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.
E539920 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 Population Health | Statement: [NYU Grossman School of Medicine, hasDepartment, Department of Population Health]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Population Health
Context triple: [NYU Grossman School of Medicine, hasDepartment, Department of Population Health]
  • A. Department of Population and Family Health
    The Department of Population and Family Health is an academic unit at Columbia University’s Mailman School of Public Health that focuses on global population dynamics, reproductive and sexual health, maternal and child health, and related public health policy and practice.
  • B. 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.
  • C. Office of Population Health
    The Office of Population Health is a division within the Massachusetts Department of Public Health that focuses on improving health outcomes and reducing health disparities across communities through data-driven policies and programs.
  • D. 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.
  • E. Department of Health Policy and Management
    The Department of Health Policy and Management is an academic unit that focuses on research and education in health policy, health systems, and healthcare management within the Mailman School of Public 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: Department of Population Health
Triple: [NYU Grossman School of Medicine, hasDepartment, Department of Population Health]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Population Health
Target entity description: 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.
  • A. Department of Population and Family Health
    The Department of Population and Family Health is an academic unit at Columbia University’s Mailman School of Public Health that focuses on global population dynamics, reproductive and sexual health, maternal and child health, and related public health policy and practice.
  • B. 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.
  • C. Office of Population Health
    The Office of Population Health is a division within the Massachusetts Department of Public Health that focuses on improving health outcomes and reducing health disparities across communities through data-driven policies and programs.
  • D. 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.
  • E. Department of Health Policy and Management
    The Department of Health Policy and Management is an academic unit that focuses on research and education in health policy, health systems, and healthcare management within the Mailman School of Public Health.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023b780248190a912d2dddbd0aa17 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a39756c819098b06911c58d50a8 completed March 22, 2026, 9:08 p.m.
NEDg Description generation batch_69c05d5cce248190abf49b02513fe06e completed March 22, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69c05e061ff88190b9387358cc8bc199 completed March 22, 2026, 9:24 p.m.
Created at: March 22, 2026, 3:44 p.m.