Triple
T20297663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Double Life of Véronique |
E505394
|
entity |
| Predicate | hasPosterColorPalette |
P48842
|
FINISHED |
| Object | green filters |
—
|
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: green filters | Statement: [The Double Life of Véronique, hasPosterColorPalette, green filters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPosterColorPalette Context triple: [The Double Life of Véronique, hasPosterColorPalette, green filters]
-
A.
hasColorInfo
chosen
Indicates that an entity is associated with specific color-related information or attributes.
-
B.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
C.
hasColorStructure
Indicates that an entity possesses a specific arrangement or pattern of colors.
-
D.
hasPantone
Indicates that one entity is associated with, or assigned, a specific Pantone color code.
-
E.
hasNumberOfColors
Indicates the quantity of distinct colors associated with an 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677095fb481909806214da4002b59 |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:16 a.m.