Triple
T24007654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle de Atocha |
E594433
|
entity |
| Predicate | hasHealthcareFacilityAlong |
P10262
|
FINISHED |
| Object | Hospital General de Atocha (historic) |
—
|
NE NERFINISHED |
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: Hospital General de Atocha (historic) | Statement: [Calle de Atocha, hasHealthcareFacilityAlong, Hospital General de Atocha (historic)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthcareFacilityAlong Context triple: [Calle de Atocha, hasHealthcareFacilityAlong, Hospital General de Atocha (historic)]
-
A.
hasHealthcareInfrastructure
Indicates that an entity possesses facilities, systems, and resources necessary to deliver healthcare services.
-
B.
hasMedicalCenter
chosen
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
C.
hasMedicalUnit
Indicates that an entity possesses, includes, or is associated with a medical unit (such as a clinic, department, or medical team) as part of its structure or resources.
-
D.
hasHealthcareServicesIn
Indicates that a healthcare provider or organization offers or operates healthcare services within a specified location or area.
-
E.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
- 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_69e288bc8f608190ac4af29f0bd1c744 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d46ba1f88190a204d8cfb0f64be6 |
completed | April 29, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:40 p.m.