Triple
T7726283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paper Concerto |
E175138
|
entity |
| Predicate | textureFocus |
P31
|
FINISHED |
| Object | unconventional textures |
—
|
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: unconventional textures | Statement: [Paper Concerto, textureFocus, unconventional textures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textureFocus Context triple: [Paper Concerto, textureFocus, unconventional textures]
-
A.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
partCFocus
Indicates that a specific part or component of an entity is the primary focus or point of attention in a given context.
-
D.
depictionFocus
Indicates that a depiction (such as an image or illustration) is primarily focused on or centered around a particular entity or subject.
-
E.
texture
Indicates the surface quality or feel of an entity as perceived by touch or appearance, such as being smooth, rough, soft, or coarse.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.