Triple
T35226056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnny Strabler |
E1017097
|
entity |
| Predicate | costumeInfluence |
P96649
|
FINISHED |
| Object | inspired youth leather-jacket fashion |
—
|
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: inspired youth leather-jacket fashion | Statement: [Johnny Strabler, costumeInfluence, inspired youth leather-jacket fashion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeInfluence Context triple: [Johnny Strabler, costumeInfluence, inspired youth leather-jacket fashion]
-
A.
costumeInspiration
chosen
Indicates that one entity serves as the creative source or model for another entity’s costume design.
-
B.
costumeContext
Indicates the situational or narrative context in which a costume is used, such as the event, setting, or role it is associated with.
-
C.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a costume.
-
D.
costumeDesignEmphasisOn
Indicates that a costume design places particular focus or priority on a specified element, style, feature, or thematic aspect.
-
E.
costumeDesignStyle
Indicates the stylistic approach or aesthetic characteristics used in designing a costume for a character or 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_69f76de072908190ab65038a8a7b6a79 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:02 p.m.