Triple
T12891158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biograph projector |
E308366
|
entity |
| Predicate | filmFormatCharacteristic |
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 projector, filmFormatCharacteristic, large-format film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmFormatCharacteristic Context triple: [Biograph projector, filmFormatCharacteristic, 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.
filmPerforationType
Indicates the specific style or pattern of perforations used along the edges of a film stock.
-
D.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
-
E.
cinematicForm
Indicates that something is expressed, structured, or realized through the techniques, conventions, or medium of cinema or 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97146d2208190be5ae26e51193b67 |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.