Triple

T16886109
Position Surface form Disambiguated ID Type / Status
Subject Ebola River E421543 entity
Predicate nearSettlement P3883 FINISHED
Object Yambuku E414772 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: Yambuku | Statement: [Ebola River, nearSettlement, Yambuku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yambuku
Context triple: [Ebola River, nearSettlement, Yambuku]
  • A. Yambuku, Zaire chosen
    Yambuku, Zaire was a small rural village in northern Zaire (now the Democratic Republic of the Congo) that became historically significant as the site of the first known outbreak of Ebola virus disease in 1976.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Ngoumbi
    Ngoumbi is an alternative name for the Kombe people, an ethnic group of Central Africa.
  • D. Lambaréné
    Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
  • E. Nkroful
    Nkroful is a village in Ghana best known as the birthplace of the country's first president and independence leader, Kwame Nkrumah.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc126e881909dae8133ad34acc9 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2bcf290819098be9def471e02b8 completed May 10, 2026, 5:39 p.m.
Created at: April 10, 2026, 5:29 a.m.