Triple

T29888767
Position Surface form Disambiguated ID Type / Status
Subject Nyayo philosophy E759087 entity
Predicate appliedInOfficeOf P194941 FINISHED
Object President of Kenya LITERAL 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: President of Kenya | Statement: [Nyayo philosophy, appliedInOfficeOf, President of Kenya]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliedInOfficeOf
Context triple: [Nyayo philosophy, appliedInOfficeOf, President of Kenya]
  • A. builtUnderOfficeOf
    Indicates that something was constructed under the authority, supervision, or jurisdiction of a particular office or official body.
  • B. hasOffice
    Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
  • C. servesAsOfficeOf
    Indicates that one entity functions as the official office, headquarters, or administrative base for another entity.
  • D. representsInOffice
    Indicates that one entity serves as an official representative of another entity within a specific office, position, or institutional role.
  • E. aboutOfficeHeld
    Indicates that one entity is related to, or provides information about, a specific office or position that is or was held by another entity.
  • F. None of above. chosen

Provenance (4 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_69f2245de2f48190a481404896b56254 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69fd91a5dad8819093eeeef527027890 completed May 8, 2026, 7:32 a.m.
PD Predicate disambiguation batch_69fd8f65fe9081908902500a3228d935 completed May 8, 2026, 7:23 a.m.
PDg Predicate description generation batch_69fd91a44268819081b372296e3aa116 completed May 8, 2026, 7:32 a.m.
Created at: April 29, 2026, 6:01 p.m.