Triple

T15985466
Position Surface form Disambiguated ID Type / Status
Subject Nakuru County E387680 entity
Predicate borders P224 FINISHED
Object Laikipia County E1086207 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: Laikipia County | Statement: [Nakuru County, borders, Laikipia County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laikipia County
Context triple: [Nakuru County, borders, Laikipia County]
  • A. Laikipia County chosen
    Laikipia County is a region in central Kenya known for its wildlife conservancies, ranches, and growing tourism and agricultural sectors.
  • B. Nyandarua County
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • 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. Tharaka-Nithi County
    Tharaka-Nithi County is a county in Kenya’s former Eastern Province, known for its proximity to Mount Kenya and its mix of highland agriculture and scenic landscapes.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157589d78819091f7b9b1081dd6ad completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c28f43988190aa06da8c356b9646 completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 4:54 a.m.