Triple
T4483337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmgreen & Dragset |
E100180
|
entity |
| Predicate | Prada MarfaType |
P56816
|
FINISHED |
| Object | permanent site-specific installation |
—
|
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: permanent site-specific installation | Statement: [Elmgreen & Dragset, Prada MarfaType, permanent site-specific installation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Prada MarfaType Context triple: [Elmgreen & Dragset, Prada MarfaType, permanent site-specific installation]
-
A.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
-
B.
partOfSkylineOf
Indicates that one entity is a visible component or feature contributing to the overall skyline profile of another entity, typically a city or urban area.
-
C.
designsFor
Indicates that one entity creates or plans something specifically intended to serve, suit, or be used by another entity.
-
D.
LeonardoDaVinciResidence
Indicates that a specified location served as a place where Leonardo da Vinci lived or resided.
-
E.
FrenchFlagship
Indicates that an entity serves as the primary or leading representative (flagship) of France in a given domain or context.
- 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_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. |
| PDg | Predicate description generation | batch_69b35727a8ac819090420bd3e2cfbcf1 |
completed | March 13, 2026, 12:15 a.m. |
Created at: March 12, 2026, 11:36 p.m.