Triple
T35002057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biograph camera |
E1009707
|
entity |
| Predicate | filmFormatType |
P86894
|
FINISHED |
| Object | large-format 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: large-format film | Statement: [Biograph camera, filmFormatType, large-format film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmFormatType Context triple: [Biograph camera, filmFormatType, large-format film]
-
A.
appearsInFilmFormat
Indicates that something is presented or occurs within a specific film format or medium of cinematic presentation.
-
B.
usesFilmFormat
chosen
Indicates that one entity employs or is recorded in a particular film format associated with the other entity.
-
C.
filmStockType
Indicates the specific type or category of photographic or motion picture film stock used or associated with an entity.
-
D.
televisionFormat
Indicates the specific type or style of television program or production format associated with an entity.
-
E.
projectionFormat
Indicates the specific technical format or method used to project visual content (such as film or digital media) onto a display surface.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7858aa5508190a07dde993b3356fc |
completed | May 3, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.