Triple
T29020390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duff Dry |
E737435
|
entity |
| Predicate | hasFictionalPackaging |
P194247
|
FINISHED |
| Object | Duff Dry can |
—
|
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 Dry can | Statement: [Duff Dry, hasFictionalPackaging, Duff Dry can]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPackaging Context triple: [Duff Dry, hasFictionalPackaging, Duff Dry can]
-
A.
hasFictionalProduct
Indicates a relationship where one entity features, offers, or includes a product that exists only in fiction or an imagined context.
-
B.
hasFictionalCollector
Indicates that an entity is associated with a fictional character who collects or curates it.
-
C.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
D.
hasFictionalSignText
Indicates that an entity bears or is associated with text appearing on a fictional sign (e.g., wording depicted on an in-universe sign).
-
E.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
- F. None of above. chosen
Provenance (4 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_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
| PDg | Predicate description generation | batch_69fd68ab21a0819096bfc4a8c14851ad |
completed | May 8, 2026, 4:38 a.m. |
Created at: April 28, 2026, 9:48 a.m.