Triple
T5528753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sea Beast |
E144992
|
entity |
| Predicate | hasBlackAndWhiteCinematography |
P13343
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Sea Beast, hasBlackAndWhiteCinematography, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBlackAndWhiteCinematography Context triple: [The Sea Beast, hasBlackAndWhiteCinematography, true]
-
A.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
-
B.
hasFilmColorType
chosen
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
C.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
-
D.
hasPhotographicConvention
Indicates that there is an established photographic style, rule, or convention governing how the related entities are visually represented in photographs.
-
E.
hasCinematicThemes
Indicates that something incorporates or is characterized by themes, motifs, or stylistic elements commonly associated with 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f8b6c348190b7d414dc1907d09a |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:34 p.m.