Triple
T8885311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Barfée |
E211513
|
entity |
| Predicate | costumeTypical |
P58290
|
FINISHED |
| Object | shorts, shirt, and contestant number badge |
—
|
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: shorts, shirt, and contestant number badge | Statement: [William Barfée, costumeTypical, shorts, shirt, and contestant number badge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeTypical Context triple: [William Barfée, costumeTypical, shorts, shirt, and contestant number badge]
-
A.
costumeType
Indicates the specific kind or category of costume associated with an entity.
-
B.
typicalCostumePattern
Indicates that one entity is the characteristic or commonly used costume pattern associated with another entity.
-
C.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a costume.
-
D.
costumeContext
Indicates the situational or narrative context in which a costume is used, such as the event, setting, or role it is associated with.
-
E.
costumeFeatures
chosen
Indicates that a costume possesses or includes specific features, attributes, or decorative elements.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc616cf8c48190a27b381e48f23377 |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:53 p.m.