Triple

T12386725
Position Surface form Disambiguated ID Type / Status
Subject Sikar district E295884 entity
Predicate hasMajorTown P316 FINISHED
Object Laxmangarh E293719 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: Laxmangarh | Statement: [Sikar district, hasMajorTown, Laxmangarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laxmangarh
Context triple: [Sikar district, hasMajorTown, Laxmangarh]
  • A. Laxmangarh chosen
    Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
  • B. Laxmangarh
    Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
  • C. Karauli
    Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
  • D. Nawalgarh
    Nawalgarh is a historic town in Rajasthan, India, renowned for its richly painted havelis and cultural heritage within the Shekhawati region.
  • E. Ramgarh
    Ramgarh is a town and administrative district headquarters in the Indian state of Jharkhand, known for its coal mining and industrial activities.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a533a2788190b885c000c29f4e87 completed May 3, 2026, 1:30 a.m.
Created at: April 8, 2026, 9:54 p.m.