Triple

T9436126
Position Surface form Disambiguated ID Type / Status
Subject RSMC Toulouse E227510 entity
Predicate typeOfEmergencySupported P77203 FINISHED
Object radiological emergencies 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: radiological emergencies | Statement: [RSMC Toulouse, typeOfEmergencySupported, radiological emergencies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfEmergencySupported
Context triple: [RSMC Toulouse, typeOfEmergencySupported, radiological emergencies]
  • A. typeOfEmergencyService
    Indicates the specific category or kind of emergency service associated with or provided in a given situation.
  • B. emergencyTypesCovered chosen
    Indicates that certain kinds of emergencies are included within the scope of coverage, protection, or response defined by the relationship.
  • C. hasEmergencyServices
    Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
  • D. hasEmergencyCare
    Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
  • E. hasEmergencySystems
    Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7ede1e148190b5793863a851c92c completed April 1, 2026, 8:23 p.m.
PD Predicate disambiguation batch_69cca55548488190b171ae695a3212de completed April 1, 2026, 4:55 a.m.
Created at: March 30, 2026, 7:50 p.m.