Triple
T28616444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GetTickCount |
E724282
|
entity |
| Predicate | returnTypeWidth |
P4121
|
FINISHED |
| Object | 32-bit unsigned integer |
—
|
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: 32-bit unsigned integer | Statement: [GetTickCount, returnTypeWidth, 32-bit unsigned integer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: returnTypeWidth Context triple: [GetTickCount, returnTypeWidth, 32-bit unsigned integer]
-
A.
encodingWidth
Indicates the width dimension used when encoding a signal, image, or data stream.
-
B.
extendedPrecisionWidth
Indicates the bit-width or size used to represent values in an extended-precision numeric format beyond standard precision.
-
C.
executionWidth
Indicates the degree of parallelism or number of concurrent units used when executing an operation or process.
-
D.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
E.
bitWidth
chosen
Indicates the number of bits used to represent or encode a given value, type, or data element.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 28, 2026, 4:32 a.m.