Triple

T26770381
Position Surface form Disambiguated ID Type / Status
Subject Reforger exercises E675059 entity
Predicate typicalOpposingForce P4567 FINISHED
Object simulated Warsaw Pact forces 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: simulated Warsaw Pact forces | Statement: [Reforger exercises, typicalOpposingForce, simulated Warsaw Pact forces]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalOpposingForce
Context triple: [Reforger exercises, typicalOpposingForce, simulated Warsaw Pact forces]
  • A. opposingForce chosen
    Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
  • B. opposingUnits
    Indicates that two units are in opposition to each other, such as being on rival sides, conflicting forces, or competing entities within a given context.
  • C. enemyForceType
    Indicates that one entity is characterized as a hostile or opposing force of a specified type relative to another entity.
  • D. primaryEnemyForces
    Indicates that the related entities constitute the main opposing or hostile forces in a conflict or competitive situation.
  • E. opposingForceDescription
    Indicates a description of a force that acts in opposition to another force or influence within a given 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_69eecda85298819097ee1c38a3d772e7 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69ff069ec1348190815375c5c9e38404 completed May 9, 2026, 10:04 a.m.
PD Predicate disambiguation batch_69ff05ba57f88190a45d20f18044e0fb completed May 9, 2026, 10 a.m.
Created at: April 27, 2026, 4:02 a.m.