Triple

T20460288
Position Surface form Disambiguated ID Type / Status
Subject División Azul E501905 entity
Predicate totalPersonnelEstimate P24266 FINISHED
Object over 40,000 Spanish volunteers served 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: over 40,000 Spanish volunteers served | Statement: [División Azul, totalPersonnelEstimate, over 40,000 Spanish volunteers served]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: totalPersonnelEstimate
Context triple: [División Azul, totalPersonnelEstimate, over 40,000 Spanish volunteers served]
  • A. militaryCasualtiesEstimate
    Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
  • B. casualtiesEstimate
    Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
  • C. personnelStrength chosen
    Indicates the number or capacity of people assigned to or available for a particular unit, organization, or operation.
  • D. commandingForceSize
    Indicates the size or magnitude of the military or organizational force that is exercising command or control in a given context.
  • E. hasApproximateNumberOfPeople
    Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
  • 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a549a48190a1bcd7a6b0f71a11 completed April 20, 2026, 9:12 p.m.
PD Predicate disambiguation batch_69e57679eb40819086142df3e39c928e completed April 20, 2026, 12:42 a.m.
Created at: April 16, 2026, 11:33 a.m.