Triple

T9936659
Position Surface form Disambiguated ID Type / Status
Subject BK117 D-2 E193975 entity
Predicate typicalMedicalCrew P21064 FINISHED
Object 1 or 2 medical staff 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: 1 or 2 medical staff | Statement: [BK117 D-2, typicalMedicalCrew, 1 or 2 medical staff]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalMedicalCrew
Context triple: [BK117 D-2, typicalMedicalCrew, 1 or 2 medical staff]
  • A. crewType chosen
    Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
  • B. hasMedicalCorps
    Indicates that an entity possesses, maintains, or is associated with an organized medical corps or medical service unit.
  • C. rescueCasualties
    Indicates performing actions to locate, assist, and remove injured or endangered individuals from a hazardous or emergency situation.
  • D. chiefMedicalOfficer
    Indicates that one entity serves as the highest-ranking medical authority or head of medical operations for the other entity.
  • E. crew
    Indicates that one entity serves as the group of people who operate, staff, or work on another entity (such as a vehicle, vessel, or production).
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5e4e19881909879b394090d6629 completed April 2, 2026, 12:18 a.m.
PD Predicate disambiguation batch_69cd1d9428cc81909b4b4938566d78a7 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:44 p.m.