Triple

T7741769
Position Surface form Disambiguated ID Type / Status
Subject A. H. M. Khairuzzaman Liton E175525 entity
Predicate officeJurisdiction P6190 FINISHED
Object Rajshahi E32151 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: Rajshahi | Statement: [A. H. M. Khairuzzaman Liton, officeJurisdiction, Rajshahi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rajshahi
Context triple: [A. H. M. Khairuzzaman Liton, officeJurisdiction, Rajshahi]
  • A. Rajshahi chosen
    Rajshahi is a prominent city in western Bangladesh, known as an important cultural, educational, and commercial center of the Bengal region.
  • B. Barisal
    Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
  • C. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • D. Savar
    Savar is a suburban area near Dhaka in Bangladesh, known for its educational institutions, industrial zones, and historical significance.
  • E. Chittagong
    Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7035df9348190ad3f3d845207bf4d completed March 27, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca65545c3c819080a4bf7945871e5d completed March 30, 2026, 11:58 a.m.
Created at: March 27, 2026, 4:07 p.m.