Triple
T5400425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl Hines |
E120758
|
entity |
| Predicate | teachingInfluence |
P10669
|
FINISHED |
| Object | later generations of jazz pianists |
—
|
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: later generations of jazz pianists | Statement: [Earl Hines, teachingInfluence, later generations of jazz pianists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingInfluence Context triple: [Earl Hines, teachingInfluence, later generations of jazz pianists]
-
A.
educationalImpact
chosen
Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
-
B.
coreTeaching
Indicates that an entity serves as a primary or foundational teaching or instructional activity for another entity.
-
C.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
D.
notableTeaching
Indicates that one entity is recognized for having taught, instructed, or educated another entity in a notable or significant way.
-
E.
taughtThat
Indicates that one entity provided instruction or education to another entity about a specific subject, skill, or concept.
- 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.