Triple
T12107213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MGM Camera 65 |
E288332
|
entity |
| Predicate | usesFilmStockType |
P86894
|
FINISHED |
| Object | 65 mm negative film |
—
|
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: 65 mm negative film | Statement: [MGM Camera 65, usesFilmStockType, 65 mm negative film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFilmStockType Context triple: [MGM Camera 65, usesFilmStockType, 65 mm negative film]
-
A.
usesFilmFormat
chosen
Indicates that one entity employs or is recorded in a particular film format associated with the other entity.
-
B.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
C.
hasFilmSetType
Indicates that a film or scene is associated with a particular type or category of set used in its production.
-
D.
typeOfStills
Indicates that one entity is a specific kind or category of stills (e.g., a particular type or style within the broader class of still images or still photography).
-
E.
usesCameraType
Indicates that one entity employs or operates a specific type or category of camera.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.