Triple

T3155719
Position Surface form Disambiguated ID Type / Status
Subject Paris–Los Angeles E65980 entity
Predicate timeZonesCrossed P3413 FINISHED
Object multiple 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 | Statement: [Paris–Los Angeles, timeZonesCrossed, multiple]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeZonesCrossed
Context triple: [Paris–Los Angeles, timeZonesCrossed, multiple]
  • A. timeZoneDependence
    Indicates how a process, value, or behavior changes or is determined based on the time zone in which it is considered.
  • B. timeZonePractice
    Indicates that an entity conducts activities or operations according to a particular time zone or set of time zone rules.
  • C. hasTimeZones chosen
    Indicates that an entity is associated with one or more time zones in which it is valid or operates.
  • D. relatedTimeZone
    Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
  • E. hasNumberOfNationalTimeZones
    Indicates the quantity of distinct official time zones that a nation or country uses within its territory.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5e97548819084643586fff2e3cb completed March 8, 2026, 4:38 p.m.
PD Predicate disambiguation batch_69ad9dfbf0348190952a6bca8fc5fed1 completed March 8, 2026, 4:04 p.m.
Created at: March 8, 2026, 3:05 p.m.