Triple
T11089698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Name Medical Center |
E262217
|
entity |
| Predicate | hasCardiologyServices |
P77388
|
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: [Holy Name Medical Center, hasCardiologyServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCardiologyServices Context triple: [Holy Name Medical Center, hasCardiologyServices, yes]
-
A.
hasClinicalService
chosen
Indicates that an entity provides, offers, or is associated with a specific clinical service.
-
B.
hasCardiacCareUnit
Indicates that an entity (such as a hospital or medical facility) includes or is equipped with a specialized cardiac care unit for treating heart-related conditions.
-
C.
hasDiagnosticService
Indicates that an entity provides, is associated with, or makes use of a diagnostic service for detecting, analyzing, or identifying issues or conditions.
-
D.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
E.
hasHealthcareInfrastructure
Indicates that an entity possesses facilities, systems, and resources necessary to deliver healthcare services.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799e96ca08190838c8a04d1eb2a16 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.