Triple

T8073887
Position Surface form Disambiguated ID Type / Status
Subject Barisal Division E188443 entity
Predicate capital P234 FINISHED
Object Barisal E183865 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: Barisal | Statement: [Barisal Division, capital, Barisal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barisal
Context triple: [Barisal Division, capital, Barisal]
  • A. Barisal chosen
    Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
  • B. Comilla
    Comilla is a major city in eastern Bangladesh known for its historical sites, educational institutions, and role as a regional commercial hub.
  • 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. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • E. Rajshahi
    Rajshahi is a prominent city in western Bangladesh, known as an important cultural, educational, and commercial center of the Bengal region.
  • 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_69ca82b50c708190863f661d438e68df completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb404a98408190b6c8eecb95ad086d completed March 31, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce020086788190be74e8e97d87013d completed April 2, 2026, 5:43 a.m.
Created at: March 30, 2026, 5:27 p.m.