Triple
T25425684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyrix 486 |
E637109
|
entity |
| Predicate | fabricationModel |
P76106
|
FINISHED |
| Object | fabless design model |
—
|
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: fabless design model | Statement: [Cyrix 486, fabricationModel, fabless design model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fabricationModel Context triple: [Cyrix 486, fabricationModel, fabless design model]
-
A.
manufacturingModel
Indicates that one entity serves as the manufacturing model, design, or template according to which another entity is produced or manufactured.
-
B.
fabricationTechnology
chosen
Indicates the manufacturing or production method used to create or realize an entity.
-
C.
producedModel
Indicates that one entity created, manufactured, or generated the other entity as a model or product.
-
D.
designModel
Indicates that one entity creates, specifies, or defines the structure or behavior of another entity as a model or blueprint.
-
E.
fabricationPartner
Indicates a relationship where one entity serves as a manufacturing or production collaborator responsible for fabricating another entity’s designs, components, or products.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6bfdb748190abfd40ed1838d9aa |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:57 p.m.