Triple

T8941302
Position Surface form Disambiguated ID Type / Status
Subject Moses Wetang'ula E212905 entity
Predicate residence P75 FINISHED
Object Bungoma County E768593 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: Bungoma County | Statement: [Moses Wetang'ula, residence, Bungoma County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bungoma County
Context triple: [Moses Wetang'ula, residence, Bungoma County]
  • A. Bungoma County chosen
    Bungoma County is an administrative region in western Kenya known for its agricultural economy and as a political stronghold in the former Western Province.
  • B. Mpigi District
    Mpigi District is an administrative district in central Uganda known for its agricultural activities and proximity to the capital, Kampala.
  • C. 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.
  • D. Nyanga District
    Nyanga District is an administrative district in northeastern Zimbabwe known for its mountainous landscapes and popular tourist attractions such as Nyanga National Park.
  • E. 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.
  • 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_69ca839694c88190b324ffeb43d23b08 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66b9c14c8190b80c3df0cdba2747 completed April 1, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc93a1e4c8190b33478783dcd09d7 completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:58 p.m.