Triple

T16914562
Position Surface form Disambiguated ID Type / Status
Subject Council of Ministers of Bangladesh E410288 entity
Predicate seat P75 FINISHED
Object Dhaka E26021 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: Dhaka | Statement: [Council of Ministers of Bangladesh, seat, Dhaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dhaka
Context triple: [Council of Ministers of Bangladesh, seat, Dhaka]
  • A. Dhaka chosen
    Dhaka is the capital and largest city of Bangladesh, serving as the country’s political, economic, and cultural center.
  • B. Dhaka
    Dhaka is a town in the East Champaran district of Bihar, India, known as a local administrative and commercial center in the region.
  • C. Chittagong
    Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
  • D. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • E. Greater Dhaka
    Greater Dhaka is the densely populated metropolitan region centered on Bangladesh’s capital city, Dhaka, encompassing its urban core and surrounding suburban and peri-urban areas.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3f1a2c8190a512ccc09a080eb4 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfd0ff2881908686678daab46664 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:30 a.m.