Triple
T8940357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utrecht Chair |
E212883
|
entity |
| Predicate | hasAestheticQuality |
P16367
|
FINISHED |
| Object | minimalist appearance |
—
|
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: minimalist appearance | Statement: [Utrecht Chair, hasAestheticQuality, minimalist appearance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAestheticQuality Context triple: [Utrecht Chair, hasAestheticQuality, minimalist appearance]
-
A.
hasArtFeature
Indicates that an entity possesses or is characterized by a particular artistic attribute, element, or stylistic feature.
-
B.
hasArtisticGenre
Indicates that an entity (such as a work or creation) belongs to or is characterized by a particular artistic genre.
-
C.
hasArtisticFocus
Indicates that an entity’s primary artistic attention, theme, or specialization is directed toward a particular subject, style, or medium.
-
D.
artisticCharacteristic
chosen
Indicates that one entity possesses or exhibits a particular artistic quality, style, or trait in relation to another.
-
E.
hasPerceptualQuality
Indicates that something possesses a particular sensory or perceptual characteristic, such as a color, sound, texture, taste, or smell.
- 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b8b37c8190bce6e049de8cf732 |
completed | April 1, 2026, 12:28 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:58 p.m.