Triple

T3976276
Position Surface form Disambiguated ID Type / Status
Subject Nakuru E85650 entity
Predicate locatedIn P40 FINISHED
Object Nakuru County E387680 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: Nakuru County | Statement: [Nakuru, locatedIn, Nakuru County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakuru County
Context triple: [Nakuru, locatedIn, Nakuru County]
  • A. Nakuru County chosen
    Nakuru County is a region in Kenya’s Rift Valley known for its lakes, wildlife, and agricultural activities.
  • B. 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.
  • C. Narok County
    Narok County is a county in southwestern Kenya known for its vast savannah landscapes, rich Maasai culture, and world-famous wildlife tourism.
  • D. 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.
  • E. Taita-Taveta County
    Taita-Taveta County is a county in southeastern Kenya known for its wildlife-rich national parks, including Tsavo East and Tsavo West, and its location near the Tanzanian 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_69aed93908348190a26c8aaf4fab3e86 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9b6d8008190822fceabe6542b3d completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5401ac15481908ab86c8ef48ce413 completed March 14, 2026, 11:01 a.m.
Created at: March 9, 2026, 3:33 p.m.