Triple

T28393996
Position Surface form Disambiguated ID Type / Status
Subject South African telephone numbering plan E719233 entity
Predicate mobileNumberPrefixPattern P110648 FINISHED
Object 06X 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: 06X | Statement: [South African telephone numbering plan, mobileNumberPrefixPattern, 06X]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mobileNumberPrefixPattern
Context triple: [South African telephone numbering plan, mobileNumberPrefixPattern, 06X]
  • A. mobileNumbersHaveNoGeographicAreaCode
    Indicates that mobile phone numbers are not associated with or constrained by any specific geographic area code.
  • B. nationalPrefixForDomesticCalls
    Indicates the dialing prefix that must be used when making domestic telephone calls within a given country or numbering plan.
  • C. mobilePrefixExample chosen
    Indicates that the subject is an example or sample instance of a mobile phone number prefix associated with the object.
  • D. associatedCountryCodePrefix
    Indicates that one entity has a country code prefix that is associated with, or corresponds to, the other entity.
  • E. internationalPrefix
    Indicates that one entity is the international dialing prefix used to place telephone calls from the other entity’s country to foreign destinations.
  • 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_69eff6efd1b08190ae3cefd4f11388a2 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64cee303081908e27fadd6ef248b1 completed May 2, 2026, 7:13 p.m.
PD Predicate disambiguation batch_69f641e2f1708190b45b48d6a43c51d2 completed May 2, 2026, 6:26 p.m.
Created at: April 28, 2026, 1:15 a.m.