Triple
T361260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Düsseldorf school of painting |
E7858
|
entity |
| Predicate | teachingEmphasis |
P6235
|
FINISHED |
| Object | academic drawing |
—
|
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: academic drawing | Statement: [Düsseldorf school of painting, teachingEmphasis, academic drawing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingEmphasis Context triple: [Düsseldorf school of painting, teachingEmphasis, academic drawing]
-
A.
educationalFocus
chosen
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
-
B.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
C.
educationalApproach
Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
-
D.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
E.
educationTrend
Indicates a pattern or direction of change over time in some aspect of education, such as participation, attainment, or performance.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebce64c88190a0a8edcc7095f78b |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95c843c8190b2aba9af6e869ba1 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.