Triple
T28287859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Pierre Brisset (artist) |
E713335
|
entity |
| Predicate | creativeWorkCharacteristic |
P188879
|
FINISHED |
| Object | imaginative imagery |
—
|
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: imaginative imagery | Statement: [Jean-Pierre Brisset (artist), creativeWorkCharacteristic, imaginative imagery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creativeWorkCharacteristic Context triple: [Jean-Pierre Brisset (artist), creativeWorkCharacteristic, imaginative imagery]
-
A.
creativeWorkFocus
Indicates that one entity is the primary subject, theme, or focal point of another entity’s creative work.
-
B.
bookCharacteristic
Indicates that a particular characteristic, feature, or attribute is associated with a given book.
-
C.
notableWorkAspect
Indicates a specific characteristic, feature, or component that is a significant or defining part of a notable work.
-
D.
creativeWorkType
Indicates the specific category or form of a creative work (such as book, movie, painting, or song) that characterizes the relationship.
-
E.
creativeWorkOn
Indicates a relationship where an entity has created, contributed to, or worked on a particular creative work (such as a book, artwork, film, or other intellectual product).
- 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_69efb52371d88190a1381c4e58a3b731 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fbaf18085481908c774e8f8bbb9a41 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaebbb7f88190b4edfd9b83550aad |
completed | May 6, 2026, 9:12 p.m. |
Created at: April 27, 2026, 11:27 p.m.