Triple

T34593268
Position Surface form Disambiguated ID Type / Status
Subject Frederiksberg Hospital E888241 entity
Predicate hasInfectionControl P150442 FINISHED
Object yes 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: yes | Statement: [Frederiksberg Hospital, hasInfectionControl, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasInfectionControl
Context triple: [Frederiksberg Hospital, hasInfectionControl, yes]
  • A. hasInfectionControlMeasures chosen
    Indicates that appropriate procedures or actions are in place to prevent, reduce, or control the spread of infection.
  • B. infectionRequires
    Indicates that the occurrence or establishment of an infection depends on the presence or fulfillment of a specified condition, factor, or prerequisite.
  • C. healthcareWorkerInfectionsApproximate
    Indicates that the number of infections among healthcare workers is an approximate or estimated value rather than an exact count.
  • D. hasPrecautionaryFacility
    Indicates that an entity is equipped with or associated with a facility intended to provide precautionary or protective measures against potential risks or hazards.
  • E. hasIsolationRooms
    Indicates that the entity includes one or more rooms specifically designated and equipped for isolation purposes.
  • 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_69f349d3bfcc81909874c99e646fb3ea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 completed May 10, 2026, 7:54 a.m.
PD Predicate disambiguation batch_6a0038e525448190a4c815f51595e78d completed May 10, 2026, 7:51 a.m.
Created at: May 1, 2026, 2:03 a.m.