Triple

T12384914
Position Surface form Disambiguated ID Type / Status
Subject Rupsha River E295837 entity
Predicate region P40 FINISHED
Object Khulna Division E180941 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: Khulna Division | Statement: [Rupsha River, region, Khulna Division]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khulna Division
Context triple: [Rupsha River, region, Khulna Division]
  • A. Khulna Division chosen
    Khulna Division is an administrative region in southwestern Bangladesh known for the city of Khulna and its proximity to the Sundarbans mangrove forest.
  • B. Khulna District
    Khulna District is an administrative region in southwestern Bangladesh known for its proximity to the Sundarbans mangrove forest and its role as an important industrial and riverine hub.
  • C. Barisal Division
    Barisal Division is an administrative region in southern Bangladesh known for its extensive river networks and deltaic landscape.
  • D. 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.
  • E. 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.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbc3f608190b0ee3c4f304a94db completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556240f48190a3510d10ab98127b completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:54 p.m.