Triple
T36063212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Broken Oath |
E1043143
|
entity |
| Predicate | hasVisualPresentation |
P99801
|
FINISHED |
| Object | monochrome cinematography |
—
|
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: monochrome cinematography | Statement: [The Broken Oath, hasVisualPresentation, monochrome cinematography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualPresentation Context triple: [The Broken Oath, hasVisualPresentation, monochrome cinematography]
-
A.
hasVisualIndicator
Indicates that an entity is associated with some form of visual cue or marker that signals its status, condition, or presence.
-
B.
hasPresentation
Indicates that an entity delivers, contains, or is associated with a specific presentation (such as a talk, slide deck, or formal display of information).
-
C.
hasVisualCharacter
chosen
Indicates that one entity possesses or exhibits a particular visual appearance, style, or graphical characteristic defined by another entity.
-
D.
hasVisualImpact
Indicates that one entity affects or influences the visual appearance or aesthetic perception of another.
-
E.
isNonVisual
Indicates that the subject lacks visual characteristics or is not intended to be perceived visually.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
Created at: May 3, 2026, 4:08 p.m.