Triple

T37485921
Position Surface form Disambiguated ID Type / Status
Subject Lorengau General Hospital E931529 entity
Predicate hasDisasterResponseRole P103649 FINISHED
Object health emergencies in Manus Province 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: health emergencies in Manus Province | Statement: [Lorengau General Hospital, hasDisasterResponseRole, health emergencies in Manus Province]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDisasterResponseRole
Context triple: [Lorengau General Hospital, hasDisasterResponseRole, health emergencies in Manus Province]
  • A. hasDisaster
    Indicates that an entity experiences, is affected by, or is associated with a disaster event.
  • B. postDisasterRole chosen
    Indicates the role or function an entity assumes or performs in the aftermath of a disaster.
  • C. hasReliefEffortFrom
    Indicates that a party receives assistance or support through a relief effort provided by another party.
  • D. roleInDisasterPrevention
    Indicates that an entity has a specific function, responsibility, or involvement in activities aimed at preventing or mitigating disasters.
  • E. supportsDisasterType
    Indicates that one entity is capable of handling, responding to, or being applicable to a specified type of disaster.
  • 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_69f76ec382248190b47844df596123c6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69ff9a25407c81909faa86e72a7a9d17 completed May 9, 2026, 8:33 p.m.
PD Predicate disambiguation batch_69ff99c613688190a03b2f93d5ccad2b completed May 9, 2026, 8:32 p.m.
Created at: May 3, 2026, 4:17 p.m.