Triple
T13797167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fountain |
E331546
|
entity |
| Predicate | visualEffectsStyle |
P104064
|
FINISHED |
| Object | minimal CGI |
—
|
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: minimal CGI | Statement: [The Fountain, visualEffectsStyle, minimal CGI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualEffectsStyle Context triple: [The Fountain, visualEffectsStyle, minimal CGI]
-
A.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
B.
videoStyle
Indicates the stylistic characteristics or presentation format applied to a video (such as tone, visual approach, or editing style).
-
C.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
D.
transparencyEffects
Indicates how the level or presence of transparency in one entity influences the perception, behavior, or properties of another entity.
-
E.
specialEffectsTechnique
chosen
Indicates a relationship where a particular special effects method or process is used to create or enhance visual or auditory effects in a production.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025be1f08190aac525d72d7dc0c3 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:11 p.m.