Triple

T36401502
Position Surface form Disambiguated ID Type / Status
Subject Arusha Regional Commissioner’s Office E896642 entity
Predicate officeHoldersRole P131089 FINISHED
Object Regional Commissioner of Arusha 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: Regional Commissioner of Arusha | Statement: [Arusha Regional Commissioner’s Office, officeHoldersRole, Regional Commissioner of Arusha]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: officeHoldersRole
Context triple: [Arusha Regional Commissioner’s Office, officeHoldersRole, Regional Commissioner of Arusha]
  • A. officeHoldersHaveRole chosen
    Indicates that individuals or entities holding an office possess or are assigned a specific role associated with that office.
  • B. officeHolderRoleFor
    Indicates that a specific role or position is held by an office holder within an organization or governing body.
  • C. officeHolderRoleIn
    Indicates that an entity holds or has held a specific role or position within a particular office or organizational context.
  • D. officeHolderOf
    Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
  • E. officeHolderOccupation
    Indicates that the occupation describes the role or job held by an office holder.
  • F. None of above.

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_69f76e53b81081908d3b81860593f38a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_6a001adc8c108190ab3a43f6415e2be3 completed May 10, 2026, 5:42 a.m.
PD Predicate disambiguation batch_6a001a290330819097c2c3123f9014b4 completed May 10, 2026, 5:39 a.m.
Created at: May 3, 2026, 4:10 p.m.