Triple

T13363109
Position Surface form Disambiguated ID Type / Status
Subject Naro Moru route E318868 entity
Predicate accessTown P36630 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: [Naro Moru route, accessTown, Nanyuki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanyuki
Context triple: [Naro Moru route, accessTown, 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69da628affd081909f1790d333f0eef4 completed April 11, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f74615b0f08190a8eb8d8a87cb7053 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 9:32 p.m.