Triple

T858912
Position Surface form Disambiguated ID Type / Status
Subject Japanese 3rd Division E18555 entity
Predicate militaryUnitType P6154 FINISHED
Object infantry 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: infantry | Statement: [Japanese 3rd Division, militaryUnitType, infantry]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: militaryUnitType
Context triple: [Japanese 3rd Division, militaryUnitType, infantry]
  • A. typeOfTroops chosen
    Indicates the specific category or kind of military forces involved in or associated with an entity or event.
  • B. militaryOrganization
    Indicates that an entity functions as, or is associated with, a structured armed forces or defense-related organization.
  • C. militaryFunction
    Indicates a relationship where an entity serves a specific role, duty, or operational purpose within a military context.
  • D. militaryCharacteristic
    Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
  • E. groundForces
    Indicates that one entity deploys, commands, or involves military forces operating on land in relation to another entity or context.
  • 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_69a4938bdd3c8190a954a3c11844d9cf completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac50e5ec81908ac0c4b7123b4ebb completed March 1, 2026, 9:14 p.m.
PD Predicate disambiguation batch_69a4aa834a588190bca4a0eb83fb3eb6 completed March 1, 2026, 9:07 p.m.
Created at: March 1, 2026, 7:39 p.m.