Triple

T745202
Position Surface form Disambiguated ID Type / Status
Subject Bundeswehr E15325 entity
Predicate typeOfForces P1062 FINISHED
Object professional military 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: professional military | Statement: [Bundeswehr, typeOfForces, professional military]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfForces
Context triple: [Bundeswehr, typeOfForces, professional military]
  • A. forceType chosen
    Indicates the specific kind or category of force involved in an interaction or event (e.g., physical, legal, military, or other defined force classifications).
  • B. inForceIn
    Indicates that a rule, law, agreement, or condition is currently valid and operative within a specified jurisdiction, context, or time frame.
  • C. opposingForce
    Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
  • D. forceDirection
    Indicates the direction in which a force is applied or exerted in the relationship between entities.
  • E. inForce
    Indicates that a rule, law, agreement, or condition is currently valid, active, and being applied or enforced.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a61217b881908592096b1edacb8a completed March 1, 2026, 8:48 p.m.
PD Predicate disambiguation batch_69a4a4ff10608190bfd60b4a1cb38f7d completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.