Triple

T8941315
Position Surface form Disambiguated ID Type / Status
Subject Kiambu County E212906 entity
Predicate capital P234 FINISHED
Object Kiambu 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 | Statement: [Kiambu County, capital, Kiambu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiambu
Context triple: [Kiambu County, capital, Kiambu]
  • 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
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • C. 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.
  • D. Nyandarua County
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • 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_69ca839694c88190b324ffeb43d23b08 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66b9c14c8190b80c3df0cdba2747 completed April 1, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc93a1e4c8190b33478783dcd09d7 completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:58 p.m.