Triple

T23299236
Position Surface form Disambiguated ID Type / Status
Subject Nyeri County E590255 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Nyeri NE NERFINISHED

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: Nyeri | Statement: [Nyeri County, hasUrbanCenter, Nyeri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyeri
Context triple: [Nyeri County, hasUrbanCenter, Nyeri]
  • A. Nyeri chosen
    Nyeri is a major town in Kenya known as an administrative, commercial, and agricultural hub in the central highlands near Mount Kenya.
  • B. Nyer
    Nyer is a small commune in the Pyrénées-Orientales department of southern France, known for its mountainous landscape and location in the historic region of Conflent.
  • C. Niheu
    Niheu is a figure in Hawaiian mythology known from traditional legends and chants as a human hero involved in complex familial and divine relationships.
  • D. Nekede
    Nekede is a suburban community in Imo State, Nigeria, known for hosting the Federal Polytechnic Nekede and lying on the outskirts of the city of Owerri.
  • E. Naristi
    The Naristi were an ancient Germanic tribe known primarily from Roman sources as neighbors of the Marcomanni in Central Europe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e25d1c0ecc8190a355aa229f06d0e0 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f196d133448190bf350a9f51c1531c completed April 29, 2026, 5:27 a.m.
Created at: April 17, 2026, 5:03 p.m.