Triple
T19393020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Made in L.A. biennial |
E485113
|
entity |
| Predicate | artScene |
P136276
|
FINISHED |
| Object | Los Angeles contemporary art scene |
—
|
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: Los Angeles contemporary art scene | Statement: [Made in L.A. biennial, artScene, Los Angeles contemporary art scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artScene Context triple: [Made in L.A. biennial, artScene, Los Angeles contemporary art scene]
-
A.
artwork
Indicates that one entity is an artwork created, presented, or associated with another entity (such as an artist, collection, or institution).
-
B.
artUse
Indicates that one entity uses, applies, or employs another entity within an artistic or creative context.
-
C.
artMovement
Indicates the artistic movement or style with which an artwork, artist, or cultural work is associated.
-
D.
artCategory
Indicates the classification relationship where an artwork is assigned to a particular artistic category or genre.
-
E.
artSpecialty
Indicates that an entity’s primary focus, expertise, or specialization is in a particular art form or artistic domain.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b468dd88190acd82b4ee33bd39b |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69e50213571881909cd7543a43b51986 |
completed | April 19, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.