Triple

T13194432
Position Surface form Disambiguated ID Type / Status
Subject Hôpital d'instruction des armées Clermont-Tonnerre E314074 entity
Predicate hasInfectionControlProgram P58392 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: [Hôpital d'instruction des armées Clermont-Tonnerre, hasInfectionControlProgram, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasInfectionControlProgram
Context triple: [Hôpital d'instruction des armées Clermont-Tonnerre, hasInfectionControlProgram, yes]
  • A. hasHealthProgram chosen
    Indicates that an entity provides, administers, or is associated with a specific health-related program or initiative.
  • B. hasPublicHealthInfrastructure
    Indicates that an entity possesses systems, facilities, and organizational structures dedicated to protecting and promoting public health.
  • C. hasBiosafetyLevel
    Indicates that an entity (such as a facility, lab, or area) is assigned a specific biosafety level that defines the containment and safety measures required for handling biological agents there.
  • D. haveJointCommission
    Indicates that two or more entities share a formally established joint commission or committee between them.
  • E. healthcareWorkerInfectionsApproximate
    Indicates that the number of infections among healthcare workers is an approximate or estimated value rather than an exact count.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf054f88190b05ced98d5a22a62 completed April 10, 2026, 11:51 p.m.
PD Predicate disambiguation batch_69d98bc6bc108190b5a6a265bf6e9fd4 completed April 10, 2026, 11:46 p.m.
Created at: April 9, 2026, 9:16 p.m.