Triple
T10513032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canvas 2D API |
E247962
|
entity |
| Predicate | drawingModel |
P94310
|
FINISHED |
| Object | immediate mode |
—
|
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: immediate mode | Statement: [Canvas 2D API, drawingModel, immediate mode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drawingModel Context triple: [Canvas 2D API, drawingModel, immediate mode]
-
A.
designModel
Indicates that one entity creates, specifies, or defines the structure or behavior of another entity as a model or blueprint.
-
B.
draws
Indicates that one entity creates a visual representation or image of another entity.
-
C.
graphics
Indicates a relationship where one entity is responsible for creating, providing, or handling visual representations or graphical content for another entity or context.
-
D.
drawsLesson
Indicates that one entity derives or infers a lesson or conclusion from another entity or situation.
-
E.
sketchType
Indicates the specific kind or category of sketch associated with an entity or action.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509ca214481909b3ed9265e7a6704 |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:27 p.m.