Triple
T26523402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punky Brewster |
E670620
|
entity |
| Predicate | notableOutfitElement |
P143842
|
FINISHED |
| Object | mismatched shoes |
—
|
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: mismatched shoes | Statement: [Punky Brewster, notableOutfitElement, mismatched shoes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableOutfitElement Context triple: [Punky Brewster, notableOutfitElement, mismatched shoes]
-
A.
notableOutfit
Indicates that an entity is known for or associated with wearing a particular outfit or style of clothing.
-
B.
costumeNotability
Indicates that an entity is notable, recognized, or distinguished specifically for its costume or attire.
-
C.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
D.
alsoWornIn
Indicates that an item of clothing or accessory is additionally worn in another context, location, or time beyond the primary one mentioned.
-
E.
fashionItem
chosen
Indicates that one entity is a fashion-related product or accessory associated with, used by, or worn by another 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: April 27, 2026, 1:29 a.m.