Triple

T5997260
Position Surface form Disambiguated ID Type / Status
Subject Ahsanullah Engineering College E133501 entity
Predicate cityServed P82 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: [Ahsanullah Engineering College, cityServed, Dhaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dhaka
Context triple: [Ahsanullah Engineering College, cityServed, Dhaka]
  • A. Dhaka chosen
    Dhaka is the capital and largest city of Bangladesh, serving as the country’s political, economic, and cultural center.
  • B. Chittagong
    Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
  • C. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • D. Dhaka District
    Dhaka District is an administrative region in central Bangladesh that encompasses the nation’s capital city and serves as a major political, economic, and cultural hub.
  • 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_69c00870ddbc81909880fa3864f4f38d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04ee274e08190b6478c7ae318ae48 completed March 22, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11cdec5608190ad093a09acd32ebf completed March 23, 2026, 10:58 a.m.
Created at: March 22, 2026, 4:05 p.m.