Triple

T23396116
Position Surface form Disambiguated ID Type / Status
Subject Beni Airport E559362 entity
Predicate cityServed P82 FINISHED
Object Beni 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 | Statement: [Beni Airport, cityServed, Beni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beni
Context triple: [Beni Airport, cityServed, Beni]
  • A. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • B. Beni chosen
    Beni is a city in the eastern Democratic Republic of the Congo that became internationally known as a major hotspot of conflict and public health crises, including serving as the epicenter of the 2018–2020 Kivu Ebola epidemic.
  • C. Beni
    Beni is a town in western Nepal that serves as a gateway to the Dhaulagiri and Annapurna mountain regions.
  • D. Banzebi
    Banzebi are a subgroup of the Nzebi people, an ethnic community primarily found in Central Africa, especially in Gabon and surrounding regions.
  • E. Urambo
    Urambo is a town and district headquarters in western Tanzania known historically for tobacco production and its location within the Tabora Region.
  • 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_69e24549610c8190a069d6411ce5f661 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a4dc48008190bdcf92f8d9a5232d completed April 29, 2026, 6:27 a.m.
Created at: April 17, 2026, 5:36 p.m.