Triple
T32552213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney |
E832004
|
entity |
| Predicate | productionBannerFor |
P97291
|
FINISHED |
| Object | Sneakerella |
—
|
NE NERFINISHED |
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: Sneakerella | Statement: [Disney, productionBannerFor, Sneakerella]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionBannerFor Context triple: [Disney, productionBannerFor, Sneakerella]
-
A.
notableProductionBanner
chosen
Indicates that an entity is prominently associated with a specific production banner, such as a major studio or production company, in a notable or distinguishing way.
-
B.
bannerType
Indicates the specific category or style of a banner associated with an entity or context.
-
C.
productionBy
Indicates that something is created, manufactured, or generated by a particular agent, organization, or process.
-
D.
textOnBanner
Indicates that a specific piece of text is written, printed, or displayed on a banner.
-
E.
presentedUnderBanner
Indicates that something is displayed or showcased beneath or associated with a specific banner or heading.
- 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
Created at: May 1, 2026, 1:02 a.m.