Triple

T15633579
Position Surface form Disambiguated ID Type / Status
Subject Nankai segment E375879 entity
Predicate hazardPlanningFocusFor P74331 FINISHED
Object Japanese disaster management agencies 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: Japanese disaster management agencies | Statement: [Nankai segment, hazardPlanningFocusFor, Japanese disaster management agencies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hazardPlanningFocusFor
Context triple: [Nankai segment, hazardPlanningFocusFor, Japanese disaster management agencies]
  • A. emergencyPlanningFocus chosen
    Indicates that the primary emphasis or subject of emergency planning activities is directed toward a particular entity or aspect.
  • B. hazardScope
    Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
  • C. hazardManagementConcern
    Indicates a relationship where one entity is a source, subject, or focus of concern regarding the identification, assessment, or control of hazards by another entity.
  • D. hazardType
    Indicates the specific kind or category of hazard associated with an entity or situation.
  • E. hasEmergencyPlanningZone
    Indicates that an entity is associated with a designated emergency planning zone within which specific preparedness and response measures apply.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eb7338881909f3c430bb73f91d1 completed April 16, 2026, 2:51 a.m.
PD Predicate disambiguation batch_69deda868d4481908f4bce1c64d2902a completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:14 a.m.