Triple
T24444297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernest Goes to School |
E616357
|
entity |
| Predicate | hasScreenComedyStyle |
P45834
|
FINISHED |
| Object | physical comedy |
—
|
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: physical comedy | Statement: [Ernest Goes to School, hasScreenComedyStyle, physical comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScreenComedyStyle Context triple: [Ernest Goes to School, hasScreenComedyStyle, physical comedy]
-
A.
hasComedyElements
chosen
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
B.
hasTheatricalStyle
Indicates that one entity possesses, exhibits, or is characterized by a particular theatrical style associated with another entity.
-
C.
hasScreenplayStyle
Indicates that an entity is associated with or characterized by a particular style or manner of screenplay writing.
-
D.
hasFilmStyle
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
E.
hasComedyShows
Indicates that one entity offers, features, or includes comedy shows associated with another entity.
- 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_69e2d7edca608190aafefc8877a1b4da |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29851e6cc8190a8f160cbed4e9ab0 |
completed | April 29, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:17 a.m.