Triple

T10924492
Position Surface form Disambiguated ID Type / Status
Subject Kisii District E258030 entity
Predicate namedAfter P63 FINISHED
Object Kisii town E258030 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: Kisii town | Statement: [Kisii District, namedAfter, Kisii town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kisii town
Context triple: [Kisii District, namedAfter, Kisii town]
  • A. Kabete
    Kabete is a prominent town in Kenya’s Central Region, situated within Kiambu County and known for its agricultural activity and proximity to Nairobi.
  • B. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • C. Thika
    Thika is a major industrial and commercial town in central Kenya, known for its manufacturing sector and proximity to Nairobi.
  • D. Kisii District chosen
    Kisii District was a former administrative district in southwestern Kenya, inhabited mainly by the Kisii (Abagusii) people and centered around the town of Kisii.
  • E. Nakuru
    Nakuru is a prominent Kenyan city in the Rift Valley region, known for its proximity to Lake Nakuru National Park and its role as an important agricultural and commercial center.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7708f7ab48190b60a4bb8fdb17c8e completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3740b7ed081908623ae286271fb55 completed April 18, 2026, 12:07 p.m.
Created at: April 8, 2026, 9:22 p.m.