Triple

T13445721
Position Surface form Disambiguated ID Type / Status
Subject Voi E320476 entity
Predicate locatedIn P40 FINISHED
Object Taita-Taveta County E375328 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: Taita-Taveta County | Statement: [Voi, locatedIn, Taita-Taveta County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taita-Taveta County
Context triple: [Voi, locatedIn, Taita-Taveta County]
  • A. Taita-Taveta County chosen
    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.
  • 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. Nyandarua County
    Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
  • 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. 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaef5f610819092cad33ef72075ff completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0d591648190beb4430c6b199eb8 completed May 3, 2026, 9:40 p.m.
Created at: April 9, 2026, 9:40 p.m.