Triple
T18564677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Base64 |
E453732
|
entity |
| Predicate | usesCharacterSetSize |
P58060
|
FINISHED |
| Object | 64 |
—
|
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: 64 | Statement: [Base64, usesCharacterSetSize, 64]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCharacterSetSize Context triple: [Base64, usesCharacterSetSize, 64]
-
A.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
characterSetSize
chosen
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
C.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
D.
hasDistinctCharacterSet
Indicates that two compared items use different sets of characters, with no character set being a subset or duplicate of the other.
-
E.
usesCharactersAs
Indicates that one entity employs or incorporates specific characters (such as letters, symbols, or glyphs) from another entity for its representation or functioning.
- 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.