Triple
T13816753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Make 'Em Laugh |
E332038
|
entity |
| Predicate | hasSettingInFilm |
P52439
|
FINISHED |
| Object | film studio backstage |
—
|
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: film studio backstage | Statement: [Make 'Em Laugh, hasSettingInFilm, film studio backstage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettingInFilm Context triple: [Make 'Em Laugh, hasSettingInFilm, film studio backstage]
-
A.
hasFilmSetType
Indicates that a film or scene is associated with a particular type or category of set used in its production.
-
B.
filmSetting
chosen
Indicates the place, time, or environment in which the events of a film are set or take place.
-
C.
hasFilmStyle
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
D.
hasInteractiveFilm
Indicates that an entity is associated with, offers, or features an interactive film experience.
-
E.
basedOnInFilm
Indicates that a film is derived from, adapted from, or otherwise uses as its source material another work, event, or concept.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0281bb988190803ee195f430b9c8 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.