Triple

T12161669
Position Surface form Disambiguated ID Type / Status
Subject Jhunjhunu district E289722 entity
Predicate contains P35 FINISHED
Object Nawalgarh E975397 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: Nawalgarh | Statement: [Jhunjhunu district, contains, Nawalgarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nawalgarh
Context triple: [Jhunjhunu district, contains, Nawalgarh]
  • A. Nawalgarh chosen
    Nawalgarh is a historic town in Rajasthan, India, renowned for its richly painted havelis and cultural heritage within the Shekhawati region.
  • B. Naraingarh
    Naraingarh is a town in the northern Indian state of Haryana, known for its agricultural surroundings and role as a local commercial center.
  • C. Kishangarh
    Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
  • D. Nagaur
    Nagaur is a historic city in Rajasthan, India, known for its medieval fort, cultural heritage, and role as an important center in the Marwar region.
  • E. Laxmangarh
    Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c395e48190a16e97fd29787a51 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65e9868ec81909efd7e142d5fb090 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:50 p.m.