Triple

T15366478
Position Surface form Disambiguated ID Type / Status
Subject Venezuelan Standard Time E367426 entity
Predicate isWholeHourOffset P118297 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: [Venezuelan Standard Time, isWholeHourOffset, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isWholeHourOffset
Context triple: [Venezuelan Standard Time, isWholeHourOffset, true]
  • A. hasHalfHourOffset
    Indicates that one entity’s time zone differs from another’s by an offset that includes a 30-minute (half-hour) component.
  • B. hasNonIntegerHourOffset
    Indicates that the time-related value or time zone differs from a reference time by an offset that is not a whole number of hours (e.g., includes 30- or 45-minute increments).
  • C. isHalfHourTimeZone
    Indicates that a time zone has an offset from Coordinated Universal Time (UTC) that differs by a half-hour increment rather than a whole hour.
  • D. usesQuarterHourOffset
    Indicates that the time zone or time representation applies a UTC offset that differs from whole hours by a quarter hour (15 minutes).
  • E. hasTimeOffset
    Indicates that one temporal value is shifted or displaced from another by a specified amount of time.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4a7cdc8190b7b48c97e774c306 completed April 16, 2026, 1:41 a.m.
PD Predicate disambiguation batch_69deca9ab7e88190a9261ef27be665b1 completed April 14, 2026, 11:15 p.m.
PDg Predicate description generation batch_69decf2e413481909d9180a8d78d2c17 completed April 14, 2026, 11:35 p.m.
Created at: April 10, 2026, 3:18 a.m.