Triple

T21558494
Position Surface form Disambiguated ID Type / Status
Subject Mojeño E531953 entity
Predicate locatedIn P40 FINISHED
Object Beni Department NE NERFINISHED

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: [Mojeño, locatedIn, Beni Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beni Department
Context triple: [Mojeño, 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. Bamboutos Department
    Bamboutos Department is an administrative division in western Cameroon known for its highland terrain and agricultural communities.
  • C. Lopé Department
    Lopé Department is an administrative division in central Gabon known for encompassing parts of the ecologically rich Lopé National Park.
  • D. Cuvette Department
    Cuvette Department is an administrative region in the northern part of the Republic of the Congo, known for its forests, rivers, and role as the birthplace of several prominent Congolese figures.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eed2e14af88190bc70b4d0f3453aac completed April 27, 2026, 3:07 a.m.
Created at: April 16, 2026, 6:29 p.m.