Triple

T5966675
Position Surface form Disambiguated ID Type / Status
Subject Khandesh E132769 entity
Predicate historicalCapital P2536 FINISHED
Object Burhanpur E114025 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: Burhanpur | Statement: [Khandesh, historicalCapital, Burhanpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burhanpur
Context triple: [Khandesh, historicalCapital, Burhanpur]
  • A. Burhanpur chosen
    Burhanpur is a historic city in central India known for its Mughal-era architecture and strategic location on the banks of the Tapti River.
  • B. Baharampur
    Baharampur is a major town and administrative center in the Murshidabad district of the Indian state of West Bengal, known for its historical significance and regional commerce.
  • C. Babatpur
    Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
  • D. Rampurhat
    Rampurhat is a town and important railway junction in the Birbhum district of West Bengal, India.
  • E. Buxar
    Buxar is a historic town in the Indian state of Bihar, best known as the site of a pivotal 1764 battle that cemented British colonial dominance in northern India.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3e06848190b1d1a191db257a07 completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3ff62f08190be56bb9c450c9647 completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:03 p.m.