Triple

T8526652
Position Surface form Disambiguated ID Type / Status
Subject Udaipur State E201834 entity
Predicate hasCity P316 FINISHED
Object Udaipur E60736 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: Udaipur | Statement: [Udaipur State, hasCity, Udaipur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Udaipur
Context triple: [Udaipur State, hasCity, Udaipur]
  • A. Udaipur chosen
    Udaipur is a historic city in India renowned for its lakes, palaces, and role as a former capital of the Mewar kingdom.
  • B. Udaipur
    Udaipur is a historic town in the Indian state of Tripura, known for its ancient temples and scenic lakes.
  • C. 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.
  • D. Jaipur
    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.
  • E. 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.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6463fe48190b6d3482212356be1 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d160f6855c81909ae0f3f1c041f600 completed April 4, 2026, 7:05 p.m.
Created at: March 30, 2026, 6:16 p.m.