Triple

T17255506
Position Surface form Disambiguated ID Type / Status
Subject SalamAir E418869 entity
Predicate cityServed P82 FINISHED
Object Chattogram 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: Chattogram | Statement: [SalamAir, cityServed, Chattogram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chattogram
Context triple: [SalamAir, cityServed, 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 (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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e6c362c819088965c6e05f33faf completed April 19, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c3ca3f08190b7da411a5638214e completed May 11, 2026, 7:58 a.m.
Created at: April 10, 2026, 5:39 a.m.