Triple

T9125716
Position Surface form Disambiguated ID Type / Status
Subject Myanmar Standard Time E218962 entity
Predicate timeOffsetInHours P87222 FINISHED
Object 6.5 — 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: 6.5 | Statement: [Myanmar Standard Time, timeOffsetInHours, 6.5]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeOffsetInHours
Context triple: [Myanmar Standard Time, timeOffsetInHours, 6.5]
  • A. timeOffsetType
    Indicates the type or category of temporal offset that specifies how one time point is shifted relative to another.
  • B. timeOffsetReference
    Indicates that a temporal value is specified relative to a particular reference time or event, defining the offset between them.
  • C. utcOffsetDescription
    Indicates the textual description of how far a time zone’s local time differs from Coordinated Universal Time (UTC), often including details like hours, minutes, and daylight saving adjustments.
  • D. offsetDSTDifferenceHours
    Indicates the difference in time zone offsets, measured in hours, that results specifically from the application of daylight saving time.
  • E. UTCOffsetDaylightSavingTime
    Indicates the time difference from Coordinated Universal Time (UTC) that applies to an entity specifically during daylight saving time periods.
  • 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_69ca83dddd548190983b96c664f7f367 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8b8970881909c3b2c67fc131627 completed April 1, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69cc66003e3c819091e1e42c9cf7c781 completed April 1, 2026, 12:25 a.m.
PDg Predicate description generation batch_69cc6a3c78388190a7436acc0e44ff55 completed April 1, 2026, 12:43 a.m.
Created at: March 30, 2026, 7:17 p.m.