Triple

T2358694
Position Surface form Disambiguated ID Type / Status
Subject TC E47217 entity
Predicate hasSubdivisionCodePrefix P22016 FINISHED
Object TC- 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: TC- | Statement: [TC, hasSubdivisionCodePrefix, TC-]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSubdivisionCodePrefix
Context triple: [TC, hasSubdivisionCodePrefix, TC-]
  • A. hasSubdivisionCode chosen
    Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
  • B. hasSubdivisionCodeContext
    Indicates that a subdivision code is interpreted within a specific coding or contextual framework that defines its meaning.
  • C. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • D. hasTypeOfSubdivision
    Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
  • E. hasDivisionCode
    Indicates that an entity is associated with a specific division identifier or code within an organizational or classification structure.
  • 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_69a88a1a4a6081908645b0f2914521ab completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc720b9048190a5d3b19e5e1f373a completed March 7, 2026, 6:35 a.m.
PD Predicate disambiguation batch_69abc599b92c819093d9e15d4437705d completed March 7, 2026, 6:28 a.m.
Created at: March 4, 2026, 7:55 p.m.