Triple

T4164149
Position Surface form Disambiguated ID Type / Status
Subject NP44 E84400 entity
Predicate hasSubdivisionExample P54206 FINISHED
Object NP44 1 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: NP44 1 | Statement: [NP44, hasSubdivisionExample, NP44 1]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSubdivisionExample
Context triple: [NP44, hasSubdivisionExample, NP44 1]
  • A. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • B. hasSubdivisionCode
    Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
  • C. hasSubdivisionStandard
    Indicates that a governing standard or specification defines how an entity is to be subdivided into smaller parts or units.
  • D. hasTypeOfSubdivision
    Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
  • E. hasHigherLevelSubdivision
    Indicates that one administrative or organizational unit is contained within and subordinate to a larger, higher-level subdivision.
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0321eee88190871c1d4bf44a5007 completed March 9, 2026, 5:28 p.m.
PD Predicate disambiguation batch_69af018dc90c8190a754b1bfbc802e80 completed March 9, 2026, 5:21 p.m.
PDg Predicate description generation batch_69af0320775c8190b90d80f512060f1c completed March 9, 2026, 5:28 p.m.
Created at: March 9, 2026, 3:44 p.m.