Triple

T22103079
Position Surface form Disambiguated ID Type / Status
Subject Special 26 E546216 entity
Predicate filmingLocation P40 FINISHED
Object Jaipur NE NERFINISHED

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: Jaipur | Statement: [Special 26, filmingLocation, Jaipur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaipur
Context triple: [Special 26, filmingLocation, Jaipur]
  • A. Jaipur chosen
    Jaipur is a major historic city in northwestern India, famed for its pink-hued architecture, royal palaces, and role as a key cultural and tourist center.
  • B. Jodhpur
    Jodhpur is a historic city in the Indian state of Rajasthan, renowned for its blue-painted old town, imposing Mehrangarh Fort, and role as a major cultural and commercial center on the edge of the Thar Desert.
  • C. Udaipur
    Udaipur is a historic town in the Indian state of Tripura, known for its ancient temples and scenic lakes.
  • D. Udaipur
    Udaipur is a town in the Lahaul and Spiti district of Himachal Pradesh, India, known for its scenic Himalayan setting and the ancient Mrikula Devi Temple.
  • E. Udaipur
    Udaipur is a historic city in India renowned for its lakes, palaces, and role as a former capital of the Mewar kingdom.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129175a7881909549883f23c53dca completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.