Triple
T977638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jurassic Park area (Universal Studios Japan) |
E21091
|
entity |
| Predicate | hasVisualStyle |
P1609
|
FINISHED |
| Object | realistic dinosaur aesthetic |
—
|
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: realistic dinosaur aesthetic | Statement: [Jurassic Park area (Universal Studios Japan), hasVisualStyle, realistic dinosaur aesthetic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualStyle Context triple: [Jurassic Park area (Universal Studios Japan), hasVisualStyle, realistic dinosaur aesthetic]
-
A.
hasSignatureVisualStyle
Indicates that an entity is characterized by a distinctive and recognizable visual style that sets it apart from others.
-
B.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
C.
hasSubstyle
Indicates that one style is a more specific or subordinate variant of another style within a hierarchical style structure.
-
D.
hasHigherStyleThan
Indicates that one entity’s style is considered superior or more fashionable than another’s.
-
E.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b47861808190be56a7bbd926e658 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.