Triple
T4483367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tino Sehgal |
E100181
|
entity |
| Predicate | artisticPracticeFeature |
P16367
|
FINISHED |
| Object | absence of physical art objects |
—
|
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: absence of physical art objects | Statement: [Tino Sehgal, artisticPracticeFeature, absence of physical art objects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artisticPracticeFeature Context triple: [Tino Sehgal, artisticPracticeFeature, absence of physical art objects]
-
A.
artisticCharacteristic
chosen
Indicates that one entity possesses or exhibits a particular artistic quality, style, or trait in relation to another.
-
B.
artisticTraining
Indicates that one entity has provided, received, or been involved in formal or informal instruction or education in the arts from or with another entity.
-
C.
artisticField
Indicates the artistic domain or creative discipline in which an entity is active or associated.
-
D.
artisticTechnique
Indicates the method, style, or process used to create or execute an artistic work.
-
E.
hasArtisticDiscipline
Indicates that one entity practices, specializes in, or is associated with a particular artistic discipline or field.
- 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_69b34553cbe48190afa8ac1cac285b86 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35728ed508190ba0e882fa62d8848 |
completed | March 13, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69b3563d63008190816e37027e761375 |
completed | March 13, 2026, 12:11 a.m. |
Created at: March 12, 2026, 11:36 p.m.