Triple

T9925496
Position Surface form Disambiguated ID Type / Status
Subject IRDT E187911 entity
Predicate offsetFromIRST P80449 FINISHED
Object +1:00 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: +1:00 | Statement: [IRDT, offsetFromIRST, +1:00]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: offsetFromIRST
Context triple: [IRDT, offsetFromIRST, +1:00]
  • A. offsetFromIranStandardTime chosen
    Indicates the time difference between a given time reference and Iran Standard Time (IRST), typically expressed as an offset in hours and minutes.
  • B. offsetFromUTC
    Indicates the time difference between a given time value and Coordinated Universal Time (UTC), typically expressed as an offset in hours and/or minutes.
  • C. offsetInSecondsFromUTC
    Indicates the time difference, measured in whole seconds, between a given time reference and Coordinated Universal Time (UTC).
  • D. offsetFromJapanStandardTime
    Indicates the time difference between a given time zone or time value and Japan Standard Time (JST), typically expressed as an offset in hours or minutes.
  • E. offsetFromIsraelStandardTime
    Indicates the time difference between a given time reference and Israel Standard Time, usually expressed as a positive or negative offset in hours or minutes.
  • 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_69ca82b22a688190b52c75bd48429c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb599e32c8190ac676fa89c131bb6 completed April 2, 2026, 12:17 a.m.
PD Predicate disambiguation batch_69cd1d90b8a8819081748f129c0c6ab6 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:43 p.m.