Triple
T25436411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | x87 FPU |
E637383
|
entity |
| Predicate | separateCoprocessorModels |
P158513
|
FINISHED |
| Object | 80287 |
—
|
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: 80287 | Statement: [x87 FPU, separateCoprocessorModels, 80287]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separateCoprocessorModels Context triple: [x87 FPU, separateCoprocessorModels, 80287]
-
A.
separateCoprocessorModels
chosen
Indicates that distinct models or representations are maintained for coprocessors, rather than sharing or combining them with other processing components.
-
B.
coprocessorNumber
Indicates the identifying number assigned to a specific coprocessor associated with a processor or system.
-
C.
numericCoprocessorSupport
Indicates that a system or processor includes and can utilize a dedicated numeric coprocessor for performing arithmetic or mathematical operations.
-
D.
numberOfModels
Indicates the quantity or count of models associated with a given entity or context.
-
E.
someModelsCoreCount
Indicates that there exists at least one model whose core count satisfies the specified condition or relation.
- 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_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:59 p.m.