Triple

T3883448
Position Surface form Disambiguated ID Type / Status
Subject Epidemiology and Prevention Section Award for Excellence in Public Health E92879 entity
Predicate associatedOrganizationSection P629 FINISHED
Object Epidemiology and Prevention Section E92883 NE FINISHED

How this triple was built (3 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: Epidemiology and Prevention Section | Statement: [Epidemiology and Prevention Section Award for Excellence in Public Health, associatedOrganizationSection, Epidemiology and Prevention Section]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Epidemiology and Prevention Section
Context triple: [Epidemiology and Prevention Section Award for Excellence in Public Health, associatedOrganizationSection, Epidemiology and Prevention Section]
  • A. Epidemiology Section chosen
    The Epidemiology Section is a professional member group within the American Public Health Association that focuses on advancing epidemiologic research, practice, and policy to improve public health.
  • B. Division of Cancer Prevention
    The Division of Cancer Prevention is a branch of the National Cancer Institute that leads research and programs focused on preventing cancer, detecting it early, and reducing cancer risk.
  • C. 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.
  • D. Division of International Epidemiology and Population Studies
    The Division of International Epidemiology and Population Studies is a research unit focused on global patterns, causes, and control of diseases and population health dynamics.
  • E. Office of Surveillance and Epidemiology
    The Office of Surveillance and Epidemiology is a U.S. FDA office responsible for monitoring the safety and effectiveness of marketed drugs and therapeutic biologics through post-market surveillance and risk assessment.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedOrganizationSection
Context triple: [Epidemiology and Prevention Section Award for Excellence in Public Health, associatedOrganizationSection, Epidemiology and Prevention Section]
  • A. associatedOrganizationFullName
    Indicates that an entity is linked to an organization by specifying the organization’s complete, official name.
  • B. organizationAssociatedWith chosen
    Indicates that there is a formal or recognized connection or affiliation between an organization and another entity.
  • C. subjectOrganization
    Indicates that one entity serves as the organization to which another entity (such as a person, work, or activity) is affiliated or belongs.
  • D. endedOrganization
    Indicates that an organization has ceased to exist or operate, marking the termination of its existence or activities.
  • E. contributingOrganization
    Indicates an organization that plays a role in creating, supporting, or otherwise contributing to the production or provision of something.
  • F. None of above.

Provenance (4 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec9029908190a7b36a3827734db1 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b512594fa081909ba2afad11f6ea59 completed March 14, 2026, 7:46 a.m.
PD Predicate disambiguation batch_69aee759609c8190985e96ec6d96dedd completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:20 p.m.