Triple
T29049749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pathécolor |
E735233
|
entity |
| Predicate | colorApplicationMethod |
P101135
|
FINISHED |
| Object | stencils cut for each color area |
—
|
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: stencils cut for each color area | Statement: [Pathécolor, colorApplicationMethod, stencils cut for each color area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorApplicationMethod Context triple: [Pathécolor, colorApplicationMethod, stencils cut for each color area]
-
A.
paintApplicationMethod
chosen
Indicates the technique or process used to apply paint to a surface.
-
B.
colorUse
Indicates that one entity uses, applies, or is associated with a particular color in its appearance, design, or representation.
-
C.
colorTreatment
Indicates that an entity has undergone a process or action that changes, enhances, or assigns its color.
-
D.
colorBehavior
Indicates how an entity’s color changes, appears, or is used under certain conditions or interactions.
-
E.
colorInfluence
Indicates how the presence or use of one color affects the perception, appearance, or impact of another.
- 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 10:07 a.m.