Triple

T25660487
Position Surface form Disambiguated ID Type / Status
Subject KMar E643362 entity
Predicate gendarmerieModel P17521 FINISHED
Object continental European 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: continental European | Statement: [KMar, gendarmerieModel, continental European]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: gendarmerieModel
Context triple: [KMar, gendarmerieModel, continental European]
  • A. guardRegiment
    Indicates that one entity serves as a protective or security regiment for another entity.
  • B. garrisonType chosen
    Indicates the specific kind or classification of military garrison associated with an entity.
  • C. isMilitaryVariantOf
    Indicates that one entity is a military-specific version or adaptation of another, typically civilian or general-purpose, entity.
  • D. garrisonOrMobilization
    Indicates that military forces are stationed at a location as a garrison or are being assembled and prepared there for mobilization.
  • E. garrisonOrCrewType
    Indicates the specific kind of garrison or crew assigned to occupy, staff, or operate a given entity.
  • 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_69e77e7e45648190a068ed3faa8016ea completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5faee68408190b602dc71ec5b83aa completed May 2, 2026, 1:23 p.m.
PD Predicate disambiguation batch_69f4807f8680819098a524158d049c63 completed May 1, 2026, 10:29 a.m.
Created at: April 21, 2026, 6:52 p.m.