Triple

T153938
Position Surface form Disambiguated ID Type / Status
Subject Global Fund to Fight AIDS, Tuberculosis and Malaria E3136 entity
Predicate hasFundingModel P59 FINISHED
Object performance-based funding 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: performance-based funding | Statement: [Global Fund to Fight AIDS, Tuberculosis and Malaria, hasFundingModel, performance-based funding]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFundingModel
Context triple: [Global Fund to Fight AIDS, Tuberculosis and Malaria, hasFundingModel, performance-based funding]
  • A. fundingModel chosen
    Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
  • B. fundedBy
    Indicates that an entity receives financial support or resources from another entity.
  • C. hasTradingModel
    Indicates that one entity uses, is governed by, or is associated with a particular trading model.
  • D. funds
    Indicates that one entity provides financial resources or monetary support to another entity or activity.
  • E. hasStakeholder
    Indicates that an entity is a stakeholder of another entity, typically having an interest, involvement, or influence in its activities or outcomes.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a258e0b11c8190b7b5cf3c354c47ce completed Feb. 28, 2026, 2:54 a.m.
PD Predicate disambiguation batch_69a2565c727c8190bca9ba6ca52f216a completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.