Triple

T2337853
Position Surface form Disambiguated ID Type / Status
Subject Andrew Holness E44351 entity
Predicate hasPoliticalOfficeScope P38306 FINISHED
Object national 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: national | Statement: [Andrew Holness, hasPoliticalOfficeScope, national]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPoliticalOfficeScope
Context triple: [Andrew Holness, hasPoliticalOfficeScope, national]
  • A. hasPoliticalRole
    Indicates that an entity holds, has held, or is assigned a specific political office, function, or position in relation to another entity or context.
  • B. isPoliticalOffice
    Indicates that the subject is a formal governmental or political position held within a public institution or authority.
  • C. isSeniorPoliticalRole
    Indicates that the role held by an entity is a high-level or senior position within a political system or organization.
  • D. hasHeldOfficeType
    Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
  • E. memberHoldsOffice
    Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
  • F. None of above. chosen

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_69a889132b488190bbb43ad4780ddd92 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6f75d888190a2e41edaa532e83f completed March 7, 2026, 6:34 a.m.
PD Predicate disambiguation batch_69abc594087c819098100a10c5478a4b completed March 7, 2026, 6:28 a.m.
PDg Predicate description generation batch_69abc6f4245881909282b3184a288e2a completed March 7, 2026, 6:34 a.m.
Created at: March 4, 2026, 7:51 p.m.