Triple
T968381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Café Terrace at Night |
E20888
|
entity |
| Predicate | has influence on |
P9
|
FINISHED |
| Object | popular culture depictions of starry night cafés |
—
|
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: popular culture depictions of starry night cafés | Statement: [Café Terrace at Night, has influence on, popular culture depictions of starry night cafés]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has influence on Context triple: [Café Terrace at Night, has influence on, popular culture depictions of starry night cafés]
-
A.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
B.
influencedDiscussionOf
Indicates that one entity had an effect on the way another entity was discussed, framed, or debated.
-
C.
influencedByCurrent
Indicates that something’s state, behavior, or outcome is affected or determined by the current conditions, context, or situation.
-
D.
influencedNameOf
Indicates that one entity has affected or shaped the naming or choice of name of another entity.
-
E.
hasSubsequentInfluence
Indicates that one entity has an influence or effect that occurs after, and is causally or temporally downstream from, another entity or event.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4481f508190adcf0a965a23862c |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a579888190afb489ac9fe8391c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.