Triple
T1250086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parkland Memorial Hospital |
E26853
|
entity |
| Predicate | traumaLevel |
P25803
|
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: [Parkland Memorial Hospital, traumaLevel, Level I adult trauma center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traumaLevel Context triple: [Parkland Memorial Hospital, traumaLevel, Level I adult trauma center]
-
A.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
B.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
C.
fatalInjury
Indicates that an entity causes or sustains an injury that directly results in death.
-
D.
eraOfIncreasedIntensity
Indicates a period during which the level or strength of a particular activity, condition, or phenomenon becomes significantly higher than before.
-
E.
bodyLevel
Indicates the relative position or height of an entity’s body (or body part) along a vertical or hierarchical scale.
- F. None of above. chosen
Provenance (4 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf84c73c8190bbb14265cd7ab6ae |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:47 p.m.