Triple
T9360981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 300 (comic series) |
E225273
|
entity |
| Predicate | coloringTechnique |
P14965
|
FINISHED |
| Object | digital coloring |
—
|
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: digital coloring | Statement: [300 (comic series), coloringTechnique, digital coloring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coloringTechnique Context triple: [300 (comic series), coloringTechnique, digital coloring]
-
A.
artisticTechnique
chosen
Indicates the method, style, or process used to create or execute an artistic work.
-
B.
colorTreatment
Indicates that an entity has undergone a process or action that changes, enhances, or assigns its color.
-
C.
colorationFunction
Indicates a relationship where an entity’s coloration serves a particular role or purpose, such as camouflage, signaling, or protection.
-
D.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
E.
colorTheory
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
- 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_69ca842bdd648190904131d58620d448 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4ff4268c819099dd5fe79d93e7ea |
completed | April 1, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.