Triple

T16728274
Position Surface form Disambiguated ID Type / Status
Subject Limuru Road E406519 entity
Predicate regionServed P82 FINISHED
Object Kiambu County E212906 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: Kiambu County | Statement: [Limuru Road, regionServed, Kiambu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiambu County
Context triple: [Limuru Road, regionServed, Kiambu County]
  • A. Kiambu County chosen
    Kiambu County is a largely peri-urban and agricultural county in central Kenya, bordering Nairobi and forming part of the greater Nairobi metropolitan area.
  • B. Kisumu County
    Kisumu County is a county in western Kenya along Lake Victoria, known as a major economic and political hub and the location of the city of Kisumu.
  • C. Kitui County
    Kitui County is a semi-arid administrative region in eastern Kenya known for its rural economy, coal deposits, and location between the coastal and central highland areas.
  • D. Nyandarua County
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • E. Nyamira County
    Nyamira County is an administrative county in western Kenya known for its predominantly Kisii community, hilly highland terrain, and tea and coffee farming.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38749baa48190892b2e2b978f6eb6 completed April 18, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0180bf3d308190b4965d57fe327a52 completed May 11, 2026, 7:09 a.m.
Created at: April 10, 2026, 5:20 a.m.