Triple

T38084741
Position Surface form Disambiguated ID Type / Status
Subject Cabinets of Hendrikus Colijn E950945 entity
Predicate implementedPolicyGoal P39536 FINISHED
Object maintaining currency stability 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: maintaining currency stability | Statement: [Cabinets of Hendrikus Colijn, implementedPolicyGoal, maintaining currency stability]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: implementedPolicyGoal
Context triple: [Cabinets of Hendrikus Colijn, implementedPolicyGoal, maintaining currency stability]
  • A. implementedPolicy
    Indicates that a particular policy has been put into effect or carried out by an entity.
  • B. hasPolicyGoal
    Indicates that an entity is associated with, or aims to achieve, a specific policy objective or target.
  • C. supportsPolicyGoal chosen
    Indicates that one entity’s actions, positions, or characteristics help advance, uphold, or contribute to achieving a specified policy goal.
  • D. policyAim
    Indicates that a policy is intended to achieve, promote, or be directed toward a particular goal or objective.
  • E. targetedPolicy
    Indicates that a policy is specifically directed at, or designed to affect, a particular subset of entities rather than applying broadly.
  • 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_69f76f03a3608190a73fd6df87c792a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc4748843c8190931432653be4890c completed May 7, 2026, 8:03 a.m.
PD Predicate disambiguation batch_69fc45646ce481908caf292ff9f06e15 completed May 7, 2026, 7:55 a.m.
Created at: May 3, 2026, 4:21 p.m.