Triple
T4864620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray W. Bliss Army Health Center |
E108737
|
entity |
| Predicate | providesUrgentCare |
P464
|
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: [Ray W. Bliss Army Health Center, providesUrgentCare, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesUrgentCare Context triple: [Ray W. Bliss Army Health Center, providesUrgentCare, yes]
-
A.
hasImmediateMedicalResponse
Indicates that an entity receives prompt medical attention or intervention immediately following an incident or onset of a medical condition.
-
B.
emergencyOffice
Indicates that an office or location serves as an emergency contact point or coordination center for urgent or crisis situations.
-
C.
hasEmergencyServices
chosen
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
D.
providesCareSetting
Indicates that one entity serves as the care environment or setting in which another entity receives or delivers care.
-
E.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d7718e48190af4c0d1abfa87795 |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.