Triple

T5297990
Position Surface form Disambiguated ID Type / Status
Subject National Police of the Republic of Vietnam E119901 entity
Predicate usedUniforms P2930 FINISHED
Object military-style uniforms 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: military-style uniforms | Statement: [National Police of the Republic of Vietnam, usedUniforms, military-style uniforms]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedUniforms
Context triple: [National Police of the Republic of Vietnam, usedUniforms, military-style uniforms]
  • A. usesUniform chosen
    Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
  • B. usedUniformColor
    Indicates that multiple entities share or employed the same uniform color in a given context.
  • C. usedUniformlyAcrossCountry
    Indicates that something is applied or practiced in the same way throughout the entire country without regional variation.
  • D. uniformizedBy
    Indicates that one entity has been made uniform, standardized, or brought into a consistent form or structure by another entity.
  • E. isNonUniform
    Indicates that the property, distribution, or structure of something varies across its domain rather than remaining constant or uniform.
  • 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_69bd446f22b88190b6a47fb91c68a3e7 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8e44e7c881909b241b2fec366038 completed March 20, 2026, 6:13 p.m.
PD Predicate disambiguation batch_69bd845097ac81909678624c4907fda4 completed March 20, 2026, 5:30 p.m.
Created at: March 20, 2026, 1:53 p.m.