Triple
T24269447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windows Western European |
E605236
|
entity |
| Predicate | hasCodeUnitSize |
P66348
|
FINISHED |
| Object | 8 bits |
—
|
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: 8 bits | Statement: [Windows Western European, hasCodeUnitSize, 8 bits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCodeUnitSize Context triple: [Windows Western European, hasCodeUnitSize, 8 bits]
-
A.
definesCodeUnitSequenceLength
Indicates that an entity specifies or determines the length of a sequence of code units (such as characters or encoded units) for another entity.
-
B.
hasUnicodeCodePoint
Indicates that a character or symbol is associated with a specific numeric Unicode code point value.
-
C.
hasCodeSpaceSize
chosen
Indicates the size or capacity of the code space associated with an entity, such as the range or number of distinct codes it can represent.
-
D.
usesCodeUnitRange
Indicates that one entity operates on or is defined in terms of a specific range of code units (e.g., character or byte positions) within another entity.
-
E.
minBytesPerCodePoint
Indicates the minimum number of bytes required to represent a single code point in the given encoding or data representation.
- 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28d58666881909f28f4d4f0f7d590 |
completed | April 29, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:07 a.m.