Triple

T2118045
Position Surface form Disambiguated ID Type / Status
Subject Kisumu E43852 entity
Predicate administrativeDivision P747 FINISHED
Object Kisumu County E43852 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: Kisumu County | Statement: [Kisumu, administrativeDivision, Kisumu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kisumu County
Context triple: [Kisumu, administrativeDivision, Kisumu County]
  • A. 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.
  • B. Nairobi County
    Nairobi County is Kenya's capital and largest urban and economic hub, encompassing the city of Nairobi and serving as the country's primary center for government, commerce, and international connectivity.
  • C. Kisumu chosen
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • D. Bomi County
    Bomi County is an administrative region in western Liberia known for its role in the country’s civil conflicts and its predominantly rural, resource-rich landscape.
  • E. Central Province, Kenya
    Central Province, Kenya was a former administrative region in central Kenya known for its fertile highlands, tea and coffee production, and predominantly Kikuyu population.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb3117c081908c5e748a869d1f9f completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae307b08148190aa201ac038ce9944 completed March 9, 2026, 2:29 a.m.
Created at: March 4, 2026, 7:44 p.m.