Triple
T6789632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Knoll |
E155899
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Adobe Systems |
E4436
|
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: Adobe Systems | Statement: [Thomas Knoll, employer, Adobe Systems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adobe Systems Context triple: [Thomas Knoll, employer, Adobe Systems]
-
A.
Adobe Inc.
chosen
Adobe Inc. is a multinational software company best known for its creative and multimedia products such as Photoshop, Illustrator, and Acrobat, widely used in digital media and design industries.
-
B.
Corel Corporation
Corel Corporation is a Canadian software company best known for products like CorelDRAW and WordPerfect.
-
C.
Macromedia
Macromedia was a pioneering software company best known for creating web and multimedia tools like Flash and Dreamweaver before being acquired by Adobe.
-
D.
Hewlett-Packard
Hewlett-Packard is a pioneering American technology company known for its innovations in computing, printers, and enterprise IT solutions.
-
E.
Apple Inc.
Apple Inc. is a multinational technology company best known for designing and selling consumer electronics like the iPhone, Mac, and iPad, along with software and digital services.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ab4ce88190b6311e4d5aac758c |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a8998408190b741417ce6f21f55 |
completed | March 28, 2026, 12:02 a.m. |
Created at: March 27, 2026, 2:15 p.m.