Triple

T28153097
Position Surface form Disambiguated ID Type / Status
Subject Legion Condor E714672 entity
Predicate trainingContribution P166863 FINISHED
Object development of Blitzkrieg tactics 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: development of Blitzkrieg tactics | Statement: [Legion Condor, trainingContribution, development of Blitzkrieg tactics]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: trainingContribution
Context triple: [Legion Condor, trainingContribution, development of Blitzkrieg tactics]
  • A. trainingComponent
    Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
  • B. trainingIn
    Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
  • C. training
    Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
  • D. trainingSupport
    Indicates that one entity provides assistance, resources, or facilitation to help another entity conduct or participate in training activities.
  • E. trainingLeadsTo
    Indicates that a process of training results in or brings about a particular outcome, state, or effect.
  • 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_69efd6b033208190bf74f80a147e2092 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f664aa283c8190a869d0555eff60c6 completed May 2, 2026, 8:55 p.m.
PD Predicate disambiguation batch_69f663362c008190a22afed262f1e426 completed May 2, 2026, 8:48 p.m.
PDg Predicate description generation batch_69f6645a615481909b53d94512ecbaf1 completed May 2, 2026, 8:53 p.m.
Created at: April 27, 2026, 10 p.m.