Triple
T12985630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America the Beautiful Quarters |
E321759
|
entity |
| Predicate | reverseDesigns |
P107903
|
FINISHED |
| Object | rotating designs |
—
|
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: rotating designs | Statement: [America the Beautiful Quarters, reverseDesigns, rotating designs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reverseDesigns Context triple: [America the Beautiful Quarters, reverseDesigns, rotating designs]
-
A.
reverseDesignSubject
Indicates that the subject is the entity for which a design or plan is derived by reversing or backtracking from an existing outcome or artifact.
-
B.
reverseDesigner
Indicates that one entity is the designer or creator of another entity, with the direction of the relationship reversed from a primary “designer” predicate.
-
C.
pairedWithReverseDesign
Indicates that an entity is associated with another entity that represents its reverse or opposite design counterpart.
-
D.
reverseMotif
Indicates that one motif is the reversed or inverted form of another motif in structure, order, or direction.
-
E.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97f1badac8190a59e60751f47b8d6 |
completed | April 10, 2026, 10:52 p.m. |
Created at: April 9, 2026, 8:40 p.m.