Triple
T607106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citation Star |
E12017
|
entity |
| Predicate | decorationType |
P2788
|
FINISHED |
| Object | device attached to ribbon |
—
|
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: device attached to ribbon | Statement: [Citation Star, decorationType, device attached to ribbon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decorationType Context triple: [Citation Star, decorationType, device attached to ribbon]
-
A.
decoration
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
-
B.
typeOfDecoration
chosen
Indicates the specific kind or style of decoration associated with an entity or applied in a given context.
-
C.
decorations
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another entity.
-
D.
furnishingType
Indicates the type or category of furnishings associated with an entity, such as a property or room.
-
E.
artworkType
Indicates the specific category or kind of artwork that characterizes the relationship between the subject and the artwork.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cf8fc1c81908a9c7df552aa1a59 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.