Triple

T15745875
Position Surface form Disambiguated ID Type / Status
Subject Rift Valley Province E381719 entity
Predicate containsCounty P5971 FINISHED
Object Uasin Gishu County E640731 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: Uasin Gishu County | Statement: [Rift Valley Province, containsCounty, Uasin Gishu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uasin Gishu County
Context triple: [Rift Valley Province, containsCounty, Uasin Gishu County]
  • A. Uasin Gishu County chosen
    Uasin Gishu County is an agriculturally rich county in Kenya’s Rift Valley region, with Eldoret as its main urban and economic center.
  • B. 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.
  • C. Kisii County
    Kisii County is an administrative county in southwestern Kenya known for its fertile highlands, intensive agriculture, and vibrant Kisii (Abagusii) community.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502d72008190b4d13a6b3a12e467 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa9361f5c8190b68702154d05bbc2 completed May 9, 2026, 9:37 p.m.
Created at: April 10, 2026, 4:46 a.m.