Triple
T3979609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maison Kammerzell |
E85723
|
entity |
| Predicate | hasDecorativeTheme |
P38145
|
FINISHED |
| Object | mythological scenes |
—
|
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: mythological scenes | Statement: [Maison Kammerzell, hasDecorativeTheme, mythological scenes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDecorativeTheme Context triple: [Maison Kammerzell, hasDecorativeTheme, mythological scenes]
-
A.
hasDecor
chosen
Indicates that one entity possesses, features, or is adorned with a particular decorative element or style.
-
B.
hasCoverArtTheme
Indicates that an item’s cover art visually represents or is characterized by a particular theme or motif.
-
C.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
D.
hasPersonalThemes
Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
-
E.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
- 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.