Triple
T9770051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Idle Class |
E237099
|
entity |
| Predicate | isBlackAndWhiteFilm |
P13343
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Idle Class, isBlackAndWhiteFilm, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBlackAndWhiteFilm Context triple: [The Idle Class, isBlackAndWhiteFilm, true]
-
A.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
-
B.
hasFilmColorType
chosen
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
C.
blackAndWhiteFilmCharacter
Indicates that a character appears in, is associated with, or belongs to a black-and-white film.
-
D.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
isSoundFilm
Indicates that a film includes synchronized recorded sound as an integral part of its presentation, rather than being a silent film.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0f1dea08190b89bcc192b068c66 |
completed | April 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69cd03d3b68c81909e570401a891b9f2 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:26 p.m.