Triple

T12986560
Position Surface form Disambiguated ID Type / Status
Subject Sirimon route E321782 entity
Predicate accessedFrom P1985 FINISHED
Object Nanyuki E324393 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: Nanyuki | Statement: [Sirimon route, accessedFrom, Nanyuki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanyuki
Context triple: [Sirimon route, accessedFrom, Nanyuki]
  • A. Nanyuki chosen
    Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
  • B. Nyamira
    Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
  • C. Kirinyaga
    Kirinyaga is the traditional name used by the Kikuyu people for Mount Kenya, reflecting its cultural and spiritual significance as the sacred mountain of brightness.
  • D. Naivasha
    Naivasha is a town in Kenya’s Rift Valley region known as a gateway to the nearby Lake Naivasha and surrounding wildlife and flower-farming areas.
  • E. Nyanga
    Nyanga is a township on the Cape Flats near Cape Town, South Africa, known for its history of apartheid-era resistance and ongoing social and economic challenges.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e5f47ec8190b39107bc016f9824 completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc277c881909ae77e8a44e06986 completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 8:40 p.m.