Triple
T2339723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Francisco VA Medical Center |
E44994
|
entity |
| Predicate | accreditedAs |
P117
|
FINISHED |
| Object | teaching hospital |
—
|
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: teaching hospital | Statement: [San Francisco VA Medical Center, accreditedAs, teaching hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accreditedAs Context triple: [San Francisco VA Medical Center, accreditedAs, teaching hospital]
-
A.
accreditedTo
Indicates that official recognition, authorization, or credit for something is granted by or associated with a particular entity.
-
B.
mayAlsoBeAccreditedTo
Indicates that the credit or attribution for something can additionally be assigned to another entity beyond the primary one.
-
C.
accreditation
chosen
Indicates that an authoritative body has formally recognized an entity as meeting specified standards or requirements.
-
D.
accreditingBody
Indicates that an entity serves as the official organization that grants accreditation or formal recognition to another entity.
-
E.
scopeOfAccreditation
Indicates the specific range, domains, or activities for which an entity’s accreditation or formal recognition is valid and applicable.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.