Triple
T25087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penn Presbyterian Medical Center |
E500
|
entity |
| Predicate | hasEmergencyDepartment |
P464
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Penn Presbyterian Medical Center, hasEmergencyDepartment, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyDepartment Context triple: [Penn Presbyterian Medical Center, hasEmergencyDepartment, true]
-
A.
hasEmergencyServices
chosen
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
B.
servesAsPrimaryTeachingHospitalFor
Indicates that one institution functions as the main clinical training and teaching site for another institution, typically a medical school or academic program.
-
C.
isTeachingHospitalFor
Indicates that one institution serves as a clinical training site or educational facility for another, typically a medical school or health education program.
-
D.
hasNotableFacility
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
-
E.
isPartOfAcademicHealthSystem
Indicates that an entity belongs to, or is organizationally integrated within, a larger academic health system.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.