Triple

T5191368
Position Surface form Disambiguated ID Type / Status
Subject Sylhet E117161 entity
Predicate partOf P40 FINISHED
Object Sylhet Region E507311 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: Sylhet Region | Statement: [Sylhet, partOf, Sylhet Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylhet Region
Context triple: [Sylhet, partOf, Sylhet Region]
  • A. Sylhet Division chosen
    Sylhet Division is an administrative region in northeastern Bangladesh known for its tea gardens, lush hills, and significant cultural and economic importance.
  • B. Sylhet
    Sylhet is a historically and culturally significant city and region in northeastern Bangladesh, known for its tea gardens, lush landscapes, and role as a major economic and spiritual center.
  • C. Barisal Division
    Barisal Division is an administrative region in southern Bangladesh known for its extensive river networks and deltaic landscape.
  • D. Rangpur Division
    Rangpur Division is an administrative region in northern Bangladesh known for its agricultural economy, historic towns, and location along major rivers including the Teesta.
  • E. Chittagong Division
    Chittagong Division is a major administrative region in southeastern Bangladesh known for its key port city, hilly landscapes, and significant rivers and waterways.
  • 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_69bd44620ff48190bcac01782107a397 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79ed61c88190bda492f6489f44de completed March 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06ac60448190a2e97a4df03863ea completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:46 p.m.