Triple

T18567816
Position Surface form Disambiguated ID Type / Status
Subject 軍教育総監 E453799 entity
Predicate 管轄分野 P69378 FINISHED
Object 軍事教育 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: 軍事教育 | Statement: [軍教育総監, 管轄分野, 軍事教育]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: 管轄分野
Context triple: [軍教育総監, 管轄分野, 軍事教育]
  • A. fieldDivision
    Indicates a relationship where a larger field or area is partitioned into smaller sections or subdivisions.
  • B. hasFieldDivision
    Indicates that one entity is organizationally divided into, or associated with, a specific field-based subdivision of another entity.
  • C. divisionFocus
    Indicates a relationship where attention, resources, or activity are specifically directed toward a particular division within a larger organization or structure.
  • D. managementJurisdiction chosen
    Indicates that one entity has formal authority or responsibility to manage, oversee, or administer another entity or domain within a defined scope or area.
  • E. governanceArea
    Indicates the geographic or jurisdictional area over which an entity has governing authority or responsibility.
  • 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53affc3e08190b4d16b5ccb0bddbc completed April 19, 2026, 8:28 p.m.
PD Predicate disambiguation batch_69e478c16e0c8190b03966aa23c395a6 completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 11:43 a.m.