Triple
T25436405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | x87 FPU |
E637383
|
entity |
| Predicate | extendedPrecisionWidth |
P158512
|
FINISHED |
| Object | 80-bit extended precision |
—
|
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: 80-bit extended precision | Statement: [x87 FPU, extendedPrecisionWidth, 80-bit extended precision]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: extendedPrecisionWidth Context triple: [x87 FPU, extendedPrecisionWidth, 80-bit extended precision]
-
A.
encodingWidth
Indicates the width dimension used when encoding a signal, image, or data stream.
-
B.
executionWidth
Indicates the degree of parallelism or number of concurrent units used when executing an operation or process.
-
C.
availableWidth
Indicates the amount of horizontal space that is currently free or usable within a given context or container.
-
D.
extensionLength
Indicates the length or magnitude of an extension from a reference point or base object.
-
E.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
- 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_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_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 1:59 p.m.