Triple
T9340262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dilios |
E224747
|
entity |
| Predicate | visualStyleContext |
P61564
|
FINISHED |
| Object | adaptation of Frank Miller's graphic novel 300 |
—
|
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: adaptation of Frank Miller's graphic novel 300 | Statement: [Dilios, visualStyleContext, adaptation of Frank Miller's graphic novel 300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualStyleContext Context triple: [Dilios, visualStyleContext, adaptation of Frank Miller's graphic novel 300]
-
A.
typicalVisualStyle
chosen
Indicates the characteristic or commonly observed visual appearance or aesthetic style associated with an entity.
-
B.
structuralStyle
Indicates the architectural or design style that characterizes the structure or form of an entity.
-
C.
editingStyle
Indicates the characteristic manner or approach used when revising, arranging, or refining content.
-
D.
colorLineContext
Indicates a relationship where the color of a line is determined or interpreted based on its surrounding contextual information or environment.
-
E.
symbolicStyle
Indicates that one entity employs or is characterized by a particular symbolic or emblematic style defined by the other 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_69ca84286fcc81909f6e7fd7a7e862a2 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bae2e2481909effc2dc89a642c5 |
completed | April 1, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:40 p.m.