Triple
T8043698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seated Nude (1908) |
E187496
|
entity |
| Predicate | usesArtisticInfluence |
P20089
|
FINISHED |
| Object | African 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: African art | Statement: [Seated Nude (1908), usesArtisticInfluence, African art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesArtisticInfluence Context triple: [Seated Nude (1908), usesArtisticInfluence, African art]
-
A.
influenceOnArt
chosen
Indicates that one entity has affected, shaped, or inspired the artistic style, content, or development of another.
-
B.
influencedArtist
Indicates that one artist has had a significant impact on the style, work, or development of another artist.
-
C.
hasArtisticFocus
Indicates that an entity’s primary artistic attention, theme, or specialization is directed toward a particular subject, style, or medium.
-
D.
inspiredByArtist
Indicates that one entity’s work, style, or creation is influenced or motivated by the artistic output or persona of another artist.
-
E.
hasArtisticGenre
Indicates that an entity (such as a work or creation) belongs to or is characterized by a particular artistic genre.
- 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_69ca82b00cb48190b59a300f70e97bd7 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f4b5e0c819092949af0f995b850 |
completed | March 31, 2026, 3:28 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:23 p.m.