Triple
T4335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hospital of the University of Pennsylvania |
E83
|
entity |
| Predicate | hasClinicalPrograms |
P178
|
FINISHED |
| Object | inpatient 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: inpatient care | Statement: [Hospital of the University of Pennsylvania, hasClinicalPrograms, inpatient care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClinicalPrograms Context triple: [Hospital of the University of Pennsylvania, hasClinicalPrograms, inpatient care]
-
A.
offersProgram
chosen
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
B.
hasAdditionalCampus
Indicates that an educational institution maintains one or more campuses in addition to its primary or main campus.
-
C.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
D.
hasDigitalInitiative
Indicates that an entity is engaged in or associated with a specific digital project, program, or transformation effort.
-
E.
hasMainCampus
Indicates that an educational institution is primarily based at or chiefly associated with a particular campus location.
- 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.