Triple

T12485245
Position Surface form Disambiguated ID Type / Status
Subject Rurrenabaque E298414 entity
Predicate locatedIn P40 FINISHED
Object Beni Department E124822 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: Beni Department | Statement: [Rurrenabaque, locatedIn, Beni Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beni Department
Context triple: [Rurrenabaque, locatedIn, Beni Department]
  • A. Beni Department chosen
    Beni Department is a large, sparsely populated administrative region in northern Bolivia known for its vast Amazonian lowlands, wetlands, and cattle ranching.
  • B. Lopé Department
    Lopé Department is an administrative division in central Gabon known for encompassing parts of the ecologically rich Lopé National Park.
  • C. Borgou Department
    Borgou Department is an administrative region in northeastern Benin known for its diverse ethnic communities, agriculture-based economy, and the major city of Parakou.
  • D. Sud Department
    Sud Department is an administrative region in southern Haiti known for its coastal cities, beaches, and agricultural activities.
  • E. Ouest Department
    Ouest Department is an administrative region in western Haiti that includes the capital city, Port-au-Prince, and serves as the country’s political and economic center.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94ddf0b6c8190aff4fe267d8f6efe completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64ba7d8bc8190acc1f0d537a5bbbb completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:56 p.m.