Triple

T19156550
Position Surface form Disambiguated ID Type / Status
Subject Beni Territory E468940 entity
Predicate hasPublicHealthIssue P4720 FINISHED
Object Ebola outbreaks in the wider Beni region 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: Ebola outbreaks in the wider Beni region | Statement: [Beni Territory, hasPublicHealthIssue, Ebola outbreaks in the wider Beni region]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPublicHealthIssue
Context triple: [Beni Territory, hasPublicHealthIssue, Ebola outbreaks in the wider Beni region]
  • A. hasHealthConcern chosen
    Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
  • B. hasHealthCode
    Indicates that an entity is associated with a specific health-related classification or status code.
  • C. hasPublicHealthInfrastructure
    Indicates that an entity possesses systems, facilities, and organizational structures dedicated to protecting and promoting public health.
  • D. publicHealthResponse
    Indicates actions and measures taken by authorities or organizations to prevent, control, or mitigate health threats within a population.
  • E. hasAssociatedDisease
    Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
  • 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5eeb9cf9081908b17073755e83554 completed April 20, 2026, 9:15 a.m.
PD Predicate disambiguation batch_69e4b9b475d88190a8c15e8eb01dbfef completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 12:06 p.m.