Triple
T32888528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veterans Administration Hospital (various episodes) |
E841268
|
entity |
| Predicate | typicalScenesInclude |
—
|
GENERATED |
| Object | Murdock interacting with medical staff |
—
|
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: typicalScenesInclude Context triple: [Veterans Administration Hospital (various episodes), typicalScenesInclude, Murdock interacting with medical staff]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
scenes
chosen
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
C.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
D.
typicalGenresIncluded
Indicates that certain genres are commonly or characteristically included as part of another entity’s usual set of genres.
-
E.
typicalStillType
Indicates that something represents the usual or characteristic form, style, or configuration that an entity typically has or uses.
- 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
Created at: May 1, 2026, 1:18 a.m.