Triple

T20413935
Position Surface form Disambiguated ID Type / Status
Subject Dindori district E500656 entity
Predicate hasSettlement P1068 FINISHED
Object Dindori town 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: Dindori town | Statement: [Dindori district, hasSettlement, Dindori town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dindori town
Context triple: [Dindori district, hasSettlement, Dindori town]
  • A. Dindori
    Dindori is a town in the Nashik district of Maharashtra, India, known for its agricultural produce and proximity to the region’s vineyards and religious sites.
  • B. Dindori chosen
    Dindori is a town and administrative center in the central Indian state of Madhya Pradesh, known for its surrounding forests, tribal communities, and proximity to natural and cultural heritage sites.
  • C. Daryapur
    Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
  • D. Tekanpur
    Tekanpur is a town in Madhya Pradesh, India, best known for hosting the Border Security Force’s main training academy.
  • E. Dharampur
    Dharampur is a legislative assembly constituency in the Dehradun district of Uttarakhand, India.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a4281048190a2b016ec16b7d203 completed April 20, 2026, 7:10 p.m.
Created at: April 16, 2026, 11:30 a.m.