Triple

T16777994
Position Surface form Disambiguated ID Type / Status
Subject Kiambu Road E407778 entity
Predicate locatedIn P40 FINISHED
Object Kiambu 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: Kiambu County | Statement: [Kiambu Road, locatedIn, Kiambu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiambu County
Context triple: [Kiambu Road, locatedIn, 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 (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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b212fc248190a8fe1124853bf16d completed April 18, 2026, 4:32 p.m.
Created at: April 10, 2026, 5:22 a.m.