Triple
T11089700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Name Medical Center |
E262217
|
entity |
| Predicate | hasImagingServices |
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, hasImagingServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImagingServices Context triple: [Holy Name Medical Center, hasImagingServices, yes]
-
A.
hasImagingType
Indicates the specific imaging modality or technique associated with or used in a given imaging procedure or result.
-
B.
hasImagingFinding
Indicates that an entity (typically a patient, case, or anatomical region) is associated with a specific observation or result identified through an imaging procedure (e.g., X-ray, CT, MRI).
-
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.
hasClinicalService
chosen
Indicates that an entity provides, offers, or is associated with a specific clinical service.
-
E.
hasLaboratoryServices
Indicates that one entity provides or makes available laboratory services to another entity or within a given context.
- 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.