Triple

T12697040
Position Surface form Disambiguated ID Type / Status
Subject Kishangarh Airport, Ajmer E303360 entity
Predicate serves P98 FINISHED
Object Kishangarh E750310 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: Kishangarh | Statement: [Kishangarh Airport, Ajmer, serves, Kishangarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kishangarh
Context triple: [Kishangarh Airport, Ajmer, serves, Kishangarh]
  • A. Kishangarh chosen
    Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
  • B. Nawalgarh
    Nawalgarh is a historic town in Rajasthan, India, renowned for its richly painted havelis and cultural heritage within the Shekhawati region.
  • C. Naraingarh
    Naraingarh is a town in the northern Indian state of Haryana, known for its agricultural surroundings and role as a local commercial center.
  • D. Kheragarh
    Kheragarh is a town in the culturally significant Braj region of northern India, known for its historical and religious associations with the broader Mathura–Agra area.
  • E. Surajgarh
    Surajgarh is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani architecture.
  • 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961ed26588190ae76ff17159e06ec completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68eafd4f8819083f20d142e9115ae completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:22 p.m.