Triple
T17786693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiss (Tino Sehgal) |
E444033
|
entity |
| Predicate | artistPracticeContext |
P128920
|
FINISHED |
| Object | non-object-based art |
—
|
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: non-object-based art | Statement: [Kiss (Tino Sehgal), artistPracticeContext, non-object-based art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artistPracticeContext Context triple: [Kiss (Tino Sehgal), artistPracticeContext, non-object-based art]
-
A.
performancePracticeContext
Indicates the situational or cultural context in which a performance is practiced, such as its conventions, conditions, and interpretive traditions.
-
B.
exhibitionPractice
Indicates the practice or method by which something is displayed or presented in an exhibition context.
-
C.
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.
-
D.
practicedWith
Indicates that one entity engaged in practice or training together with another entity.
-
E.
paintingPractice
Indicates engaging in the activity of practicing or improving skills in painting.
- F. None of above. chosen
Provenance (4 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487938418819096016ad717b014e6 |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:12 a.m.