Triple
T36565836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rita Hayworth and Fred Astaire |
E901972
|
entity |
| Predicate | typicalSettingOfFilms |
—
|
GENERATED |
| Object | contemporary urban environments |
—
|
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: typicalSettingOfFilms Context triple: [Rita Hayworth and Fred Astaire, typicalSettingOfFilms, contemporary urban environments]
-
A.
livesInFilmSetting
Indicates that an entity resides or exists within the fictional world or setting depicted in a particular film.
-
B.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
C.
filmSetting
chosen
Indicates the place, time, or environment in which the events of a film are set or take place.
-
D.
producedFilmSetIn
Indicates that a producer or production entity created a film whose story is set in a particular location or setting.
-
E.
associatedWithFictionalSetting
Indicates that an entity has a connection or relevance to a particular fictional setting or universe.
- 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_69f76e6416708190a9754b8c52d4e453 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:11 p.m.