Triple
T8469779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Schumann: Arabeske in C major, Op. 18 |
E200250
|
entity |
| Predicate | textureType |
P83478
|
FINISHED |
| Object | homophonic with figurations |
—
|
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: homophonic with figurations | Statement: [Robert Schumann: Arabeske in C major, Op. 18, textureType, homophonic with figurations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textureType Context triple: [Robert Schumann: Arabeske in C major, Op. 18, textureType, homophonic with figurations]
-
A.
texture
Indicates the surface quality or feel of an entity as perceived by touch or appearance, such as being smooth, rough, soft, or coarse.
-
B.
typicalTexture
Indicates the usual or characteristic surface feel or consistency that is commonly associated with an entity.
-
C.
primaryTexture
Indicates that one entity serves as the main or dominant surface texture characterizing another entity.
-
D.
textureTreatment
Indicates how an entity’s surface feel or texture has been modified, processed, or treated.
-
E.
textureRequirement
Indicates that one entity specifies or imposes a required texture property or characteristic that another entity must satisfy.
- F. None of above. chosen
Provenance (4 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4d5dd088190a79050417f527f14 |
completed | March 31, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69cbd10072cc819084be1ed9ac7ebe9d |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:11 p.m.