Triple
T25072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penn Presbyterian Medical Center |
E500
|
entity |
| Predicate | emergencyLevel |
P464
|
FINISHED |
| Object | Level I trauma center |
—
|
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: Level I trauma center | Statement: [Penn Presbyterian Medical Center, emergencyLevel, Level I trauma center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergencyLevel Context triple: [Penn Presbyterian Medical Center, emergencyLevel, Level I trauma center]
-
A.
hasEmergencyServices
chosen
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
B.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
C.
triggered
Indicates that one entity causes an event, action, or process involving another entity to start or occur.
-
D.
competitionLevel
Indicates the degree or intensity of competitive pressure or rivalry present in a given context or interaction.
-
E.
threatenedBy
Indicates that one entity poses a danger or potential harm to 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_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.