Triple
T6789643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Knoll |
E155899
|
entity |
| Predicate | roleInPhotoshop |
P73005
|
FINISHED |
| Object | original author of the core Photoshop code |
—
|
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: original author of the core Photoshop code | Statement: [Thomas Knoll, roleInPhotoshop, original author of the core Photoshop code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInPhotoshop Context triple: [Thomas Knoll, roleInPhotoshop, original author of the core Photoshop code]
-
A.
toolUsed
Indicates that an action or task is performed using a particular tool as the means or instrument.
-
B.
roleInEngine
Indicates the specific function or responsibility an entity has within an engine or engine-like system.
-
C.
hasPaintShop
Indicates that an entity operates, contains, or is associated with a paint shop facility or service.
-
D.
roleInAlexNet
Indicates that an entity has a specific role or function within the AlexNet neural network architecture.
-
E.
illustrator
Indicates that one entity serves as the illustrator (creator of visual artwork or drawings) for another entity, such as a book, article, or other work.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ab4ce88190b6311e4d5aac758c |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1b0d2a48190b249dcc671b9b5e4 |
completed | March 27, 2026, 6:51 p.m. |
Created at: March 27, 2026, 2:15 p.m.