Triple

T9034910
Position Surface form Disambiguated ID Type / Status
Subject Nairobi Metropolitan Region E216466 entity
Predicate containsCounty P5971 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: [Nairobi Metropolitan Region, containsCounty, Kiambu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiambu County
Context triple: [Nairobi Metropolitan Region, containsCounty, 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. Nyandarua County
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • D. Kirinyaga County
    Kirinyaga County is an administrative region in central Kenya known for its fertile agricultural land on the slopes of Mount Kenya and its production of tea, coffee, and horticultural crops.
  • E. Nakuru County
    Nakuru County is a region in Kenya’s Rift Valley known for its lakes, wildlife, and agricultural activities.
  • 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_69ca83d10b608190b2b2f8e0a7faaf14 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6abf4af481908d21245332329d99 completed April 1, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d110090f208190bf0338a37bb28e8b completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:08 p.m.