Triple
T34560479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Vincent’s Hospital, St. Augustine, Florida, United States |
E887323
|
entity |
| Predicate | hasNotablePatientDeath |
—
|
GENERATED |
| Object | Marjorie Kinnan Rawlings |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotablePatientDeath Context triple: [St. Vincent’s Hospital, St. Augustine, Florida, United States, hasNotablePatientDeath, Marjorie Kinnan Rawlings]
-
A.
hasSubjectDeathEvent
Indicates that an entity is associated with an event representing the death of its subject.
-
B.
deathOccurred
Indicates that a death event has taken place involving the specified entity or entities.
-
C.
containsDeathOf
chosen
Indicates that the subject includes, depicts, or involves the death of the referenced entity.
-
D.
hasCauseOfDeathInvestigation
Indicates that an entity is the subject of an official investigation into the circumstances or cause of its death.
-
E.
hasMannerOfDeath
Indicates the specific way or circumstances in which an entity died, such as natural causes, accident, homicide, or suicide.
- F. None of above.
Provenance (1 batch)
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_69f349d0c4d881908dd0950f5eb9ec0a |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 2:02 a.m.