Triple
T31625255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altnagelvin Area Hospital |
E807003
|
entity |
| Predicate | hasCoronaryCareUnit |
—
|
GENERATED |
| Object | yes |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoronaryCareUnit Context triple: [Altnagelvin Area Hospital, hasCoronaryCareUnit, yes]
-
A.
hasCardiacCareUnit
chosen
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.
-
B.
hasIntensiveCareUnit
Indicates that a medical facility includes and operates an intensive care unit (ICU) for critically ill patients.
-
C.
hasClinicalUnit
Indicates that an entity is associated with or belongs to a specific clinical unit or department within a healthcare setting.
-
D.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
E.
hasEmergencyDepartmentLevel
Indicates the specific classification or tier of emergency care capability associated with an emergency department.
- F. None of above.
Provenance (1 batch)
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_69f348d7883c8190b6c13ab92b7ef076 |
completed | April 30, 2026, 12:19 p.m. |
Created at: April 30, 2026, 10:43 p.m.