Triple

T13044278
Position Surface form Disambiguated ID Type / Status
Subject Close Protection Unit E327276 entity
Predicate serviceBranchSpeciality P466 FINISHED
Object military police close protection 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: military police close protection | Statement: [Close Protection Unit, serviceBranchSpeciality, military police close protection]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: serviceBranchSpeciality
Context triple: [Close Protection Unit, serviceBranchSpeciality, military police close protection]
  • A. hasSpecialty chosen
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • B. serviceBranchSpecific
    Indicates that something is restricted or tailored to a particular branch of service rather than being common across all branches.
  • C. serviceBranch
    Indicates the military or organizational branch in which an entity serves or is affiliated.
  • D. institutionSpecialization
    Indicates that an institution focuses on, is dedicated to, or has expertise in a particular field, domain, or area of activity.
  • E. openingSpecialty
    Indicates the specific area of focus, expertise, or type associated with an opening (such as a job, position, or opportunity).
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d98a9829b48190b23624b6b3df4600 completed April 10, 2026, 11:41 p.m.
PD Predicate disambiguation batch_69d9803aca4c8190b1015cd159cc47a9 completed April 10, 2026, 10:56 p.m.
Created at: April 9, 2026, 8:56 p.m.