Triple

T8941340
Position Surface form Disambiguated ID Type / Status
Subject Kiambu County E212906 entity
Predicate borders P224 FINISHED
Object Nyandarua County E723899 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: Nyandarua County | Statement: [Kiambu County, borders, Nyandarua County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyandarua County
Context triple: [Kiambu County, borders, Nyandarua County]
  • A. Nyandarua County chosen
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • B. Nakuru County
    Nakuru County is a region in Kenya’s Rift Valley known for its lakes, wildlife, and agricultural activities.
  • 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. Kiambu County
    Kiambu County is a largely peri-urban and agricultural county in central Kenya, bordering Nairobi and forming part of the greater Nairobi metropolitan area.
  • E. 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.
  • 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_69d0773aee148190ad4da1b91271e48c completed April 4, 2026, 2:28 a.m.
Created at: March 30, 2026, 6:58 p.m.