Triple
T9215009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martine Franck |
E221218
|
entity |
| Predicate | photographicTechnique |
P14965
|
FINISHED |
| Object | 35mm black-and-white 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: 35mm black-and-white film | Statement: [Martine Franck, photographicTechnique, 35mm black-and-white film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographicTechnique Context triple: [Martine Franck, photographicTechnique, 35mm black-and-white film]
-
A.
filmingTechnique
Indicates the specific method or style used to capture visual content during the filming process.
-
B.
artisticTechnique
chosen
Indicates the method, style, or process used to create or execute an artistic work.
-
C.
photographyGenre
Indicates the specific genre or style of photography that characterizes a photographic work or activity.
-
D.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
usesPhotographyFrom
Indicates that one entity employs or incorporates photographic material originating from 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda0830a8819096a186ed2e976cba |
completed | April 1, 2026, 8:40 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.