Triple

T7528595
Position Surface form Disambiguated ID Type / Status
Subject Soviet military mission in Japan E177958 entity
Predicate subjectHasOccupationContext P77347 FINISHED
Object Allied occupation of Japan 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: Allied occupation of Japan | Statement: [Soviet military mission in Japan, subjectHasOccupationContext, Allied occupation of Japan]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: subjectHasOccupationContext
Context triple: [Soviet military mission in Japan, subjectHasOccupationContext, Allied occupation of Japan]
  • A. subjectOccupation
    Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
  • B. notableOccupationContext
    Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
  • C. hasOccupationOfDesignee
    Indicates that one entity serves as the designated or appointed holder of an occupation or role for another entity.
  • D. occupationType
    Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
  • E. coversOccupation
    Indicates that one entity provides information about, includes, or pertains to another entity’s occupation or professional role.
  • F. None of above. chosen

Provenance (4 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_69c69f29bf3081909a146aec7755f185 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f81e19208190965f211d057f7fdf completed March 27, 2026, 9:35 p.m.
PD Predicate disambiguation batch_69c6f4d6bb808190bdd04499fd3bceb6 completed March 27, 2026, 9:21 p.m.
PDg Predicate description generation batch_69c6f555455c81908850210bcad96ac2 completed March 27, 2026, 9:23 p.m.
Created at: March 27, 2026, 3:47 p.m.