Triple

T23035087
Position Surface form Disambiguated ID Type / Status
Subject Air Astra E573571 entity
Predicate cityServedFromHub P81563 FINISHED
Object Chattogram NE NERFINISHED

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: Chattogram | Statement: [Air Astra, cityServedFromHub, Chattogram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chattogram
Context triple: [Air Astra, cityServedFromHub, Chattogram]
  • A. Chittagong chosen
    Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
  • B. Dhaka
    Dhaka is the capital and largest city of Bangladesh, serving as the country’s political, economic, and cultural center.
  • C. Dhaka
    Dhaka is a town in the East Champaran district of Bihar, India, known as a local administrative and commercial center in the region.
  • D. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • E. Barisal
    Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b911188190bc3d96326c847969 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1850df7fc81909ee522d99d96af0d completed April 29, 2026, 4:11 a.m.
Created at: April 17, 2026, 3:53 p.m.