Triple

T14282907
Position Surface form Disambiguated ID Type / Status
Subject Bogra Nawab family E354094 entity
Predicate hasAncestralSeat P2536 FINISHED
Object Bogra E496105 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: Bogra | Statement: [Bogra Nawab family, hasAncestralSeat, Bogra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogra
Context triple: [Bogra Nawab family, hasAncestralSeat, Bogra]
  • A. Bogra chosen
    Bogra is a major city and commercial hub in northern Bangladesh, historically part of the Bengal region.
  • B. Baria
    Baria is an alternative name for the city of Nara, an ancient cultural and historical center in Japan renowned for its temples and traditional heritage.
  • C. Bogra District
    Bogra District is an administrative region in northern Bangladesh known as a historic urban and commercial center of the Rajshahi Division.
  • D. Agargaon
    Agargaon is a prominent residential and administrative neighborhood in Dhaka, Bangladesh, known for housing several government offices and institutions.
  • E. Khanakul
    Khanakul is a town in the Hooghly district of West Bengal, India, known for its rural setting and local agricultural economy.
  • 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_69d8278d25148190abf1a8c8f5f533ad completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de697d9fd08190b0cd7a6a6737ba03 completed April 14, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d7a13288190a73683e275f6bbc0 completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:10 a.m.