Triple

T11524969
Position Surface form Disambiguated ID Type / Status
Subject Seoul–Tokyo E273268 entity
Predicate hasTimeZoneDifference P67827 FINISHED
Object 0 hours 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: 0 hours | Statement: [Seoul–Tokyo, hasTimeZoneDifference, 0 hours]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTimeZoneDifference
Context triple: [Seoul–Tokyo, hasTimeZoneDifference, 0 hours]
  • A. hasTimeOffset chosen
    Indicates that one temporal value is shifted or displaced from another by a specified amount of time.
  • B. hasTimeZones
    Indicates that an entity is associated with one or more time zones in which it is valid or operates.
  • C. hasTimeZoneNote
    Indicates that there is an associated note or annotation providing additional information or clarification about a time zone.
  • D. timeZoneDependence
    Indicates how a process, value, or behavior changes or is determined based on the time zone in which it is considered.
  • E. isBehindUTCByHours
    Indicates that one time zone or local time lags behind Coordinated Universal Time (UTC) by a specified number of hours.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d87fd379648190b342e0c4b4f685b7 completed April 10, 2026, 4:42 a.m.
PD Predicate disambiguation batch_69d80876e5f0819088cff2e72f773cf6 completed April 9, 2026, 8:13 p.m.
Created at: April 8, 2026, 9:37 p.m.