Triple
T34820035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelley Darlingson |
E1003743
|
entity |
| Predicate | knownForOutfit |
P36462
|
FINISHED |
| Object | Playboy bunny costume |
—
|
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: Playboy bunny costume | Statement: [Shelley Darlingson, knownForOutfit, Playboy bunny costume]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForOutfit Context triple: [Shelley Darlingson, knownForOutfit, Playboy bunny costume]
-
A.
notableOutfit
chosen
Indicates that an entity is known for or associated with wearing a particular outfit or style of clothing.
-
B.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
C.
typicallyWornBy
Indicates that something (such as an item or garment) is most commonly or characteristically worn by a particular type of person or group.
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
knownForCostumes
Indicates that an entity is recognized or notable specifically for its costumes, such as their design, creation, or distinctive use.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77adce5dc81909c8d07ff1c0e9c93 |
completed | May 3, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 4 p.m.