Triple
T24023731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Servicio Madrileño de Salud |
E594893
|
entity |
| Predicate | usesHealthcareModel |
P7500
|
FINISHED |
| Object | universal healthcare |
—
|
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: universal healthcare | Statement: [Servicio Madrileño de Salud, usesHealthcareModel, universal healthcare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesHealthcareModel Context triple: [Servicio Madrileño de Salud, usesHealthcareModel, universal healthcare]
-
A.
hasHealthcareServicesIn
Indicates that a healthcare provider or organization offers or operates healthcare services within a specified location or area.
-
B.
healthcareType
chosen
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
C.
hasHealthcareProvider
Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
-
D.
usesMedicalKnowledge
Indicates that an entity applies or relies on medical knowledge in performing an action or making a decision.
-
E.
medicalSystemPracticed
Indicates that a particular medical system or tradition is practiced, applied, or followed by an entity (such as a person, organization, or region).
- 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_69e288be2c288190a3a46006945557f7 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d7680d5c81908d6a670159879236 |
completed | April 29, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:52 p.m.