Triple

T1072431
Position Surface form Disambiguated ID Type / Status
Subject North Asia E23358 entity
Predicate timeZones P3413 FINISHED
Object multiple time zones 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: multiple time zones | Statement: [North Asia, timeZones, multiple time zones]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeZones
Context triple: [North Asia, timeZones, multiple time zones]
  • A. timeZoneType
    Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
  • B. hasTimeZones chosen
    Indicates that an entity is associated with one or more time zones in which it is valid or operates.
  • C. relatedTimeZone
    Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
  • D. timeZoneDependence
    Indicates how a process, value, or behavior changes or is determined based on the time zone in which it is considered.
  • E. capitalTimeZoneOf
    Indicates that a specified time zone is the primary or official time zone in which a given capital city is located or operates.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b9296c5c8190a3060fbfdf24f029 completed March 1, 2026, 10:09 p.m.
PD Predicate disambiguation batch_69a4b73844708190a16c9e9824ca2fb6 completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.