Triple
T6155886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple University Hospital |
E137318
|
entity |
| Predicate | hasTraumaDesignation |
P28274
|
FINISHED |
| Object | Level I adult 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 adult trauma center | Statement: [Temple University Hospital, hasTraumaDesignation, Level I adult trauma center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraumaDesignation Context triple: [Temple University Hospital, hasTraumaDesignation, Level I adult trauma center]
-
A.
hasCriticalDesignation
Indicates that an entity has been assigned a status or label marking it as critical in importance, priority, or required attention.
-
B.
hasTraumaCenter
chosen
Indicates that an entity (such as a hospital or facility) includes or is equipped with a designated trauma center capable of providing specialized emergency care for severe injuries.
-
C.
hasInjuredPerson
Indicates that an entity has a person who has been harmed or injured associated with it.
-
D.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
E.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
- 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d0376408190a2233375f478377e |
completed | March 22, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:17 p.m.