Triple
T6582413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murnau – Street with Women |
E157328
|
entity |
| Predicate | use of color |
P29804
|
FINISHED |
| Object | expressive |
—
|
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: expressive | Statement: [Murnau – Street with Women, use of color, expressive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: use of color Context triple: [Murnau – Street with Women, use of color, expressive]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
colorTheory
chosen
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
-
C.
colorOftenUsed
Indicates that a particular color is frequently used or commonly applied in relation to something.
-
D.
colorHasMeaning
Indicates that a particular color is associated with or conveys a specific meaning, symbolism, or significance.
-
E.
usedUniformColor
Indicates that multiple entities share or employed the same uniform color in a given 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:54 p.m.