Triple

T15745878
Position Surface form Disambiguated ID Type / Status
Subject Rift Valley Province E381719 entity
Predicate containsCounty P5971 FINISHED
Object Bomet County E865568 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: Bomet County | Statement: [Rift Valley Province, containsCounty, Bomet County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bomet County
Context triple: [Rift Valley Province, containsCounty, Bomet County]
  • A. Bomet County chosen
    Bomet County is an agricultural county in Kenya’s Rift Valley region, predominantly inhabited by the Kipsigis sub-group of the Kalenjin community.
  • B. Busia County
    Busia County is a county in western Kenya bordering Uganda, known for its diverse ethnic communities and its role as a key cross-border trade hub.
  • C. Nyeri County
    Nyeri County is a highland region in central Kenya known for its fertile agricultural land, scenic views of Mount Kenya, and as the birthplace of Nobel Peace Prize laureate Wangari Maathai.
  • D. Kisii County
    Kisii County is an administrative county in southwestern Kenya known for its fertile highlands, intensive agriculture, and vibrant Kisii (Abagusii) community.
  • E. Makueni County
    Makueni County is a semi-arid administrative region in southeastern Kenya known for its agriculture, water-scarcity challenges, and location along key transport and river basins.
  • 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_69ff8307824881909ba85e4c3da65d28 completed May 9, 2026, 6:55 p.m.
Created at: April 10, 2026, 4:46 a.m.