Triple

T18923824
Position Surface form Disambiguated ID Type / Status
Subject national colleges of family medicine E462926 entity
Predicate benefitToHealthSystem P53903 FINISHED
Object standardization of family medicine training LITERAL FINISHED

How this triple was built (2 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: standardization of family medicine training | Statement: [national colleges of family medicine, benefitToHealthSystem, standardization of family medicine training]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: benefitToHealthSystem
Context triple: [national colleges of family medicine, benefitToHealthSystem, standardization of family medicine training]
  • A. affectsBenefit
    Indicates that one entity has an influence on, modifies, or determines the benefit or advantage received by another entity.
  • B. effectOnHealthCare chosen
    Indicates the impact or influence that something has on the quality, accessibility, cost, or delivery of health care services.
  • C. benefitsCause
    Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or cause.
  • D. healthSystem
    Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
  • E. benefitsArea
    Indicates that one entity provides advantages, improvements, or positive effects to a specified area or region.
  • F. None of above.

Provenance (3 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9b549448190850d7eed4de7872b completed April 20, 2026, 6:37 a.m.
PD Predicate disambiguation batch_69e4a2e9e6488190ba8df92c8058ed88 completed April 19, 2026, 9:39 a.m.
Created at: April 10, 2026, 11:59 a.m.