Triple

T10730758
Position Surface form Disambiguated ID Type / Status
Subject Muhammad Yunus E253065 entity
Predicate birthPlace P1 FINISHED
Object Chittagong E31967 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: Chittagong | Statement: [Muhammad Yunus, birthPlace, Chittagong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chittagong
Context triple: [Muhammad Yunus, birthPlace, Chittagong]
  • A. Chittagong chosen
    Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
  • B. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • C. Barisal
    Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
  • D. Dhaka
    Dhaka is the capital and largest city of Bangladesh, serving as the country’s political, economic, and cultural 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70fcb1cd881909635def59ad5d19c completed April 9, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbda1d1b108190a47b46661bc85b2d completed April 12, 2026, 5:45 p.m.
Created at: April 8, 2026, 9:14 p.m.