Triple

T11168541
Position Surface form Disambiguated ID Type / Status
Subject Rangpur Division E264216 entity
Predicate capital P234 FINISHED
Object Rangpur E510413 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: Rangpur | Statement: [Rangpur Division, capital, Rangpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rangpur
Context triple: [Rangpur Division, capital, Rangpur]
  • A. Rangpur chosen
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • B. Chittagong
    Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
  • C. Sylhet
    Sylhet is a historically and culturally significant city and region in northeastern Bangladesh, known for its tea gardens, lush landscapes, and role as a major economic and spiritual center.
  • D. Barisal
    Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
  • E. Comilla
    Comilla is a major city in eastern Bangladesh known for its historical sites, educational institutions, and role as a regional commercial hub.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e88843cc81909e503f0921c6d297 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483747ba88190aa6ef9df2545b18b completed April 19, 2026, 7:25 a.m.
Created at: April 8, 2026, 9:29 p.m.