Triple
T4330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hospital of the University of Pennsylvania |
E83
|
entity |
| Predicate | hasFunction |
P88
|
FINISHED |
| Object | patient care |
—
|
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: patient care | Statement: [Hospital of the University of Pennsylvania, hasFunction, patient care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFunction Context triple: [Hospital of the University of Pennsylvania, hasFunction, patient care]
-
A.
hasPrimaryFunction
chosen
Indicates that one entity serves as the main or principal function or role of another entity.
-
B.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
C.
hasNotableImplementationAt
Indicates that something has a significant or noteworthy implementation located at or associated with a particular place, context, or platform.
-
D.
hasForm
Indicates that one entity possesses, exhibits, or is characterized by a particular shape, structure, or configuration.
-
E.
hasCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23c24b3d08190a714126292fd5479 |
completed | Feb. 28, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69a23998af288190855f0456740cbd51 |
completed | Feb. 28, 2026, 12:40 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.