Triple
T31386395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 24 Farben – für Blinky |
E800607
|
entity |
| Predicate | hasAbstract |
P153831
|
FINISHED |
| Object | non-representational composition |
—
|
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: non-representational composition | Statement: [24 Farben – für Blinky, hasAbstract, non-representational composition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAbstract Context triple: [24 Farben – für Blinky, hasAbstract, non-representational composition]
-
A.
hasAbstractType
Indicates that an entity is associated with or classified under a more general, conceptual type rather than a concrete or specific instance.
-
B.
includesAbstract
Indicates that one entity contains or incorporates the abstract or summary section of another entity.
-
C.
isAbstractClass
Indicates that a class is defined as abstract, meaning it cannot be instantiated directly and is intended to be subclassed.
-
D.
hasAbstractCharacter
chosen
Indicates that something possesses a non-concrete, conceptual, or intangible quality or nature rather than a physical or specific form.
-
E.
hasAbstractElements
Indicates that something contains or is composed of non-physical, conceptual, or intangible elements.
- 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_69f224e9d7048190b0cc20f9071bd3e4 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f6a0ea04888190ac3a813b603bcb5c |
completed | May 3, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:19 p.m.