Triple
T36059959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank the Rabbit |
E1043047
|
entity |
| Predicate | hasCultMerchandise |
P45835
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Frank the Rabbit, hasCultMerchandise, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCultMerchandise Context triple: [Frank the Rabbit, hasCultMerchandise, true]
-
A.
hasCulturalProduct
Indicates that an entity possesses, produces, or is associated with a cultural artifact, work, or output (such as art, literature, music, or media).
-
B.
hasCulturalObject
Indicates that one entity possesses, contains, or is associated with a cultural object (such as an artwork, artifact, or culturally significant item).
-
C.
hasExtensiveMerchandise
Indicates that an entity offers a large and varied range of merchandise or products.
-
D.
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.
-
E.
hasCraft
Indicates a relationship where an entity possesses, operates, or is associated with a particular vehicle, vessel, or other craft.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe59d11e9881909d2f33b7c717030e |
completed | May 8, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69fe394fdfbc8190a931926ae3635cbf |
completed | May 8, 2026, 7:28 p.m. |
Created at: May 3, 2026, 4:08 p.m.