Triple

T1666140
Position Surface form Disambiguated ID Type / Status
Subject Chinese Grand Prix E36015 entity
Predicate hasDRSZones P30566 FINISHED
Object yes 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: yes | Statement: [Chinese Grand Prix, hasDRSZones, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDRSZones
Context triple: [Chinese Grand Prix, hasDRSZones, yes]
  • A. hasZone
    Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
  • B. hasFreeZone
    Indicates that an entity includes or is associated with a designated free zone area where special rules, privileges, or exemptions apply.
  • C. hasFareZone
    Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
  • D. hasProtectedArea
    Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
  • E. hasRailwayZone
    Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa994f92b0819084ee2f6a672334b9 completed March 6, 2026, 9:07 a.m.
PD Predicate disambiguation batch_69a907d2475c8190b7ec7dccd3335eb1 completed March 5, 2026, 4:34 a.m.
PDg Predicate description generation batch_69a94192abc0819092fc00fef9d53bcb completed March 5, 2026, 8:40 a.m.
Created at: March 4, 2026, 7:29 p.m.