Triple
T34400740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Swan and Black Swan |
E882970
|
entity |
| Predicate | associatedWithCostume |
P28106
|
FINISHED |
| Object | white tutu |
—
|
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: white tutu | Statement: [White Swan and Black Swan, associatedWithCostume, white tutu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCostume Context triple: [White Swan and Black Swan, associatedWithCostume, white tutu]
-
A.
colorAssociatedWithCostume
Indicates that a particular color is thematically or typically linked to a specific costume.
-
B.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a costume.
-
C.
isCostumed
Indicates that an entity is wearing or otherwise adorned with a costume.
-
D.
isCostumedCharacterFor
Indicates that one entity serves as a costumed character representation or mascot for another entity, typically for promotional or entertainment purposes.
-
E.
costumeElement
chosen
Indicates that one item functions as a component or part of another item's costume.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:59 a.m.