Triple
T17878207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agate Rooms at Tsarskoye Selo |
E447011
|
entity |
| Predicate | decorativeArtsType |
P3351
|
FINISHED |
| Object | palace interior decoration |
—
|
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: palace interior decoration | Statement: [Agate Rooms at Tsarskoye Selo, decorativeArtsType, palace interior decoration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decorativeArtsType Context triple: [Agate Rooms at Tsarskoye Selo, decorativeArtsType, palace interior decoration]
-
A.
decorativeCategory
Indicates that one entity is classified as belonging to a particular decorative style, theme, or ornamentation category of another entity.
-
B.
artSpecialty
Indicates that an entity’s primary focus, expertise, or specialization is in a particular art form or artistic domain.
-
C.
decoration
chosen
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
-
D.
decorations
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another entity.
-
E.
artCategory
Indicates the classification relationship where an artwork is assigned to a particular artistic category or genre.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c0c46108190b8edef2572b5ba90 |
completed | April 19, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.