Triple
T19454945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scoops Ahoy |
E486710
|
entity |
| Predicate | hasFandomMerchandiseBasedOn |
P45835
|
FINISHED |
| Object | ice cream shop branding |
—
|
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: ice cream shop branding | Statement: [Scoops Ahoy, hasFandomMerchandiseBasedOn, ice cream shop branding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFandomMerchandiseBasedOn Context triple: [Scoops Ahoy, hasFandomMerchandiseBasedOn, ice cream shop branding]
-
A.
hasMerchandiseTieIn
chosen
Indicates that one entity has a commercial or promotional product or line (merchandise) that is directly tied to, branded with, or derived from another entity.
-
B.
usedInMerchandise
Indicates that something (such as a work, character, or design) is utilized or featured as part of a merchandise item.
-
C.
hasAnimatedFigures
Indicates that something contains or features figures that are animated or capable of motion.
-
D.
hasMediaFranchise
Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
-
E.
hasFictionalProduct
Indicates a relationship where one entity features, offers, or includes a product that exists only in fiction or an imagined context.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c2b1108190b492ca23487b91f8 |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.