Triple
T18564545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTF-16 |
E453728
|
entity |
| Predicate | minimumBytesPerCharacter |
P74323
|
FINISHED |
| Object | 2 bytes |
—
|
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: 2 bytes | Statement: [UTF-16, minimumBytesPerCharacter, 2 bytes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumBytesPerCharacter Context triple: [UTF-16, minimumBytesPerCharacter, 2 bytes]
-
A.
minBytesPerCodePoint
chosen
Indicates the minimum number of bytes required to represent a single code point in the given encoding or data representation.
-
B.
maxBytesPerCodePoint
Indicates the maximum number of bytes used to encode a single code point in a given character encoding or data representation.
-
C.
minimumFrameSize
Indicates the smallest allowable or supported size of a frame in the given context or system.
-
D.
characterSetSize
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
E.
minimumUnitSize
Indicates that there is a smallest allowable or defined size or quantity for the unit involved in the relationship.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53afd8114819093b57d86f8213311 |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:42 a.m.