Triple
T19966390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Feeley |
E479944
|
entity |
| Predicate | teachingImpact |
P10669
|
FINISHED |
| Object | development of abstract art curricula |
—
|
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: development of abstract art curricula | Statement: [Paul Feeley, teachingImpact, development of abstract art curricula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingImpact Context triple: [Paul Feeley, teachingImpact, development of abstract art curricula]
-
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.
teacherOrInfluence
Indicates that one entity serves as a teacher to, or has a significant influence on the development, behavior, or thinking of, 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.
typeOfTeaching
Indicates the specific method or style of teaching used in an instructional context.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc5e41881908c1e8867820f1c0c |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.