Triple
T24184551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelb‑Rot‑Blau |
E599519
|
entity |
| Predicate | colorTheoryRelation |
P29804
|
FINISHED |
| Object | exploration of primary colors |
—
|
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: exploration of primary colors | Statement: [Gelb‑Rot‑Blau, colorTheoryRelation, exploration of primary colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorTheoryRelation Context triple: [Gelb‑Rot‑Blau, colorTheoryRelation, exploration of primary colors]
-
A.
colorTheory
chosen
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
-
B.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
C.
colorReferenceExplains
Indicates that one color reference serves to clarify, define, or provide explanatory information about another color-related element or notation.
-
D.
colorInfluence
Indicates how the presence or use of one color affects the perception, appearance, or impact of another.
-
E.
colorDependsOn
Indicates that the color of one entity is determined or influenced by the color or properties of another entity.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:35 p.m.