Triple
T23570502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SECAmb |
E580091
|
entity |
| Predicate | providesOnSceneCare |
P59476
|
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: [SECAmb, providesOnSceneCare, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesOnSceneCare Context triple: [SECAmb, providesOnSceneCare, yes]
-
A.
providesCareSetting
Indicates that one entity serves as the care environment or setting in which another entity receives or delivers care.
-
B.
providesComprehensiveCare
Indicates that one entity delivers thorough, wide-ranging support or services addressing multiple needs of another entity.
-
C.
hasEmergencyCare
chosen
Indicates that an entity provides or is equipped with emergency medical care services for another entity or individuals.
-
D.
providesCareRegardlessOfAbilityToPay
Indicates that one party delivers care or services to another without considering or being limited by the recipient’s ability to pay.
-
E.
focusesOnMedicalCare
Indicates that one entity directs attention, resources, or activity specifically toward providing or improving medical care for another entity.
- 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_69e24601a9108190bc31e83833c980e4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1afd259e4819094b09f3ed76664ea |
completed | April 29, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:36 p.m.