Triple
T10603171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Helier Hospital |
E275802
|
entity |
| Predicate | emergencyCareCoverage |
P87982
|
FINISHED |
| Object | 24-hour |
—
|
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: 24-hour | Statement: [St Helier Hospital, emergencyCareCoverage, 24-hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergencyCareCoverage Context triple: [St Helier Hospital, emergencyCareCoverage, 24-hour]
-
A.
emergencyTypesCovered
Indicates that certain kinds of emergencies are included within the scope of coverage, protection, or response defined by the relationship.
-
B.
emergencyCareLevel
chosen
Indicates the degree or intensity of medical attention required in an emergency situation.
-
C.
emergencyUse
Indicates that something is being used in response to an urgent or critical situation, typically as a temporary or exceptional measure.
-
D.
hasEmergencyCare
Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
-
E.
emergencyService
Indicates that one entity provides or is associated with urgent, time-critical assistance or response to another entity in emergency situations.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4992248190b640d743ccf02c82 |
completed | April 8, 2026, 11:05 p.m. |
| PD | Predicate disambiguation | batch_69d6dd72c1288190adbb5e79e94c044a |
completed | April 8, 2026, 10:57 p.m. |
Created at: April 8, 2026, 7:32 p.m.