Triple

T34908467
Position Surface form Disambiguated ID Type / Status
Subject Africa/Kinshasa E1006795 entity
Predicate hasSameOffsetAllYear P136721 FINISHED
Object true 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: true | Statement: [Africa/Kinshasa, hasSameOffsetAllYear, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSameOffsetAllYear
Context triple: [Africa/Kinshasa, hasSameOffsetAllYear, true]
  • A. sameUTCOffsetAs
    Indicates that two time-related entities share the same offset from Coordinated Universal Time (UTC), regardless of their specific time zones or locations.
  • B. offsetFromUTCAllYear chosen
    Indicates that the time-related entity maintains a constant, unchanging offset from Coordinated Universal Time (UTC) throughout the entire year, without seasonal adjustments such as daylight saving time.
  • C. isSimilarOffsetTo
    Indicates that one entity has an offset or displacement that closely matches or corresponds to the offset or displacement of another entity.
  • D. hasTimeOffset
    Indicates that one temporal value is shifted or displaced from another by a specified amount of time.
  • E. isOffsetFrom
    Indicates that one entity’s position, value, or occurrence is displaced by a specified amount or direction relative to another entity.
  • 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_69f76dc1b4a081909b4c6e4d8ec0aa2d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7cec454a88190a9f3bbee2b856636 completed May 3, 2026, 10:40 p.m.
PD Predicate disambiguation batch_69f7c8977c288190997a892ec5f756ed completed May 3, 2026, 10:13 p.m.
Created at: May 3, 2026, 4 p.m.