Triple
T25436471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CISC |
E637384
|
entity |
| Predicate | exampleArchitecture |
P159124
|
FINISHED |
| Object | Motorola 68000 |
—
|
NE NERFINISHED |
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: Motorola 68000 | Statement: [CISC, exampleArchitecture, Motorola 68000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleArchitecture Context triple: [CISC, exampleArchitecture, Motorola 68000]
-
A.
exampleArchitecture
chosen
Indicates that one entity serves as a representative or illustrative instance of the architectural style, structure, or design of another entity.
-
B.
architectureName
Indicates the specific name or title assigned to an architecture.
-
C.
renderingArchitecture
Indicates the specific rendering system or framework used to generate visual output for a given entity or environment.
-
D.
architecturalConcept
Indicates that one entity represents or embodies an architectural concept in relation to another entity.
-
E.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6e0338c8190ace22e7a6239f68d |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 1:59 p.m.