Triple

T21054040
Position Surface form Disambiguated ID Type / Status
Subject Tana River County E518662 entity
Predicate borders P224 FINISHED
Object Isiolo County 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: Isiolo County | Statement: [Tana River County, borders, Isiolo County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isiolo County
Context triple: [Tana River County, borders, Isiolo County]
  • A. Isiolo County chosen
    Isiolo County is an arid, sparsely populated administrative region in northern Kenya known for its pastoralist communities, wildlife conservancies, and strategic position as a transport and trade hub.
  • B. Kajiado County
    Kajiado County is a largely semi-arid county in southern Kenya known for its Maasai communities, wildlife conservancies, and proximity to Nairobi and the Tanzania border.
  • C. Kisii County
    Kisii County is an administrative county in southwestern Kenya known for its fertile highlands, intensive agriculture, and vibrant Kisii (Abagusii) community.
  • D. Nyandarua County
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • E. Laikipia County
    Laikipia County is a region in central Kenya known for its wildlife conservancies, ranches, and growing tourism and agricultural sectors.
  • 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_69e0b5053ac48190921529544959e906 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fd7e087c81908712ddc63e8b1e6c completed April 21, 2026, 4:30 a.m.
Created at: April 16, 2026, 2:36 p.m.