Triple
T29020412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raspberry Duff |
E737436
|
entity |
| Predicate | hasFictionalBrandOwner |
P194135
|
FINISHED |
| Object | Duff Brewery |
—
|
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: Duff Brewery | Statement: [Raspberry Duff, hasFictionalBrandOwner, Duff Brewery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalBrandOwner Context triple: [Raspberry Duff, hasFictionalBrandOwner, Duff Brewery]
-
A.
hasFictionalProprietor
Indicates that something is owned, managed, or run by a fictional character or entity within a narrative context.
-
B.
hasFictionalProduct
Indicates a relationship where one entity features, offers, or includes a product that exists only in fiction or an imagined context.
-
C.
fictionalBrand
chosen
Indicates that one entity is a brand that exists only in fiction or narrative contexts, rather than in the real world.
-
D.
hasFictionalSponsor
Indicates that an entity is sponsored or endorsed by a sponsor that is fictional rather than real.
-
E.
hasFictionalCorporation
Indicates that an entity is associated with or includes a fictional corporation within its content, setting, or narrative.
- 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
Created at: April 28, 2026, 9:48 a.m.