Triple

T14922028
Position Surface form Disambiguated ID Type / Status
Subject Airkenya Express E371536 entity
Predicate hasDestination P2066 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: [Airkenya Express, hasDestination, Nanyuki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanyuki
Context triple: [Airkenya Express, hasDestination, 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. Nanyuki River
    Nanyuki River is a river in central Kenya that flows near the town of Nanyuki on the slopes of Mount Kenya, supporting local agriculture and ecosystems.
  • E. 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.
  • 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_69d85cc7ea3481908228b5acb7d06f12 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded63121e48190b54eb2546acc3c93 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72c141088190936f2fd53fee80e4 completed May 8, 2026, 11:33 p.m.
Created at: April 10, 2026, 2:34 a.m.