Triple

T3766105
Position Surface form Disambiguated ID Type / Status
Subject 1998 FIFA World Cup E82680 entity
Predicate hostCity P1798 FINISHED
Object Lens E305231 NE 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: Lens | Statement: [1998 FIFA World Cup, hostCity, Lens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lens
Context triple: [1998 FIFA World Cup, hostCity, Lens]
  • A. Lens chosen
    Lens is a commune in northern France known for its mining heritage and the Louvre-Lens art museum.
  • B. Lenses
    Lenses are Snapchat’s interactive augmented reality filters that overlay animations and effects onto users’ faces and surroundings in real time.
  • C. Barlow lenses
    Barlow lenses are optical accessories used in telescopes to effectively increase focal length and magnification by diverging the light path before it reaches the eyepiece.
  • D. Fresnel lens
    A Fresnel lens is a compact, lightweight lens design composed of concentric rings that allows lighthouses and other optical systems to project powerful, focused beams of light over long distances.
  • E. Optica
    Optica is a leading scientific society dedicated to advancing the study and application of optics and photonics worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbfeb52081909c38103beb5dbdcd completed March 8, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5221ab08190a3599afbbd5dbc6e completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.