Triple
T1774199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacPaint |
E38940
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | QuickDraw |
E38937
|
NE 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: QuickDraw | Statement: [MacPaint, basedOn, QuickDraw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: QuickDraw Context triple: [MacPaint, basedOn, QuickDraw]
-
A.
DALL·E
DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
-
B.
QuickDraw graphics system
chosen
The QuickDraw graphics system was Apple’s 2D graphics library and rendering engine that powered the visual interface and drawing operations of the classic Mac OS.
-
C.
LisaDraw
LisaDraw was a pioneering graphical drawing and diagramming application for the Apple Lisa computer, notable for its early use of a mouse-driven, WYSIWYG interface.
-
D.
The Graphic
The Graphic was a British illustrated weekly newspaper of the late 19th and early 20th centuries, renowned for its high-quality artwork and influential social commentary.
-
E.
CLIP
CLIP is an OpenAI model that learns joint representations of images and text, enabling tasks like zero-shot image classification and natural language-based image retrieval.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64b59428819082e0d43a61f4f299 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9982d208190b0c29ee1141e91b0 |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.