Triple
T8893193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Most Happy Piano |
E211734
|
entity |
| Predicate | hasInfluenceOnPerceptionOf |
P22974
|
FINISHED |
| Object | Erroll Garner as a leading jazz pianist |
—
|
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: Erroll Garner as a leading jazz pianist | Statement: [The Most Happy Piano, hasInfluenceOnPerceptionOf, Erroll Garner as a leading jazz pianist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceOnPerceptionOf Context triple: [The Most Happy Piano, hasInfluenceOnPerceptionOf, Erroll Garner as a leading jazz pianist]
-
A.
influencedPerceptionOf
chosen
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
B.
hasPublicPerception
Indicates that an entity is associated with a particular way it is viewed, judged, or regarded by the general public or society.
-
C.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
D.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
E.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
- 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_69ca83907954819096d52a245b635841 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61bb46c881909e579bb1926e5204 |
completed | April 1, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:54 p.m.