Triple
T26916301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vigenère table |
E677525
|
entity |
| Predicate | typicalAlphabetSize |
P48647
|
FINISHED |
| Object | 26 letters |
—
|
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: 26 letters | Statement: [Vigenère table, typicalAlphabetSize, 26 letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAlphabetSize Context triple: [Vigenère table, typicalAlphabetSize, 26 letters]
-
A.
alphabetSizeCondition
Indicates a constraint or requirement on the size of the alphabet used in a given context (e.g., a code, language, or symbol set).
-
B.
alphabetSizeLatin
chosen
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
C.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
D.
alphabetType
Indicates the type or classification of an alphabet used by a writing system or language.
-
E.
typicalAlpha
Indicates that an entity exhibits the characteristic or behavior considered standard or representative (i.e., “typical”) for a given group, category, or context.
- 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_69eee9bdebc48190ba90a12a63e09c73 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69ff246e0d4481908bcec718e1d4025b |
completed | May 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69ff23cb70ac81909b776ace4597ae9c |
completed | May 9, 2026, 12:08 p.m. |
Created at: April 27, 2026, 6:04 a.m.