Triple
T25602553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reed–Solomon codes |
E641825
|
entity |
| Predicate | alphabetSizeSymbol |
P58060
|
FINISHED |
| Object | q |
—
|
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: q | Statement: [Reed–Solomon codes, alphabetSizeSymbol, q]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alphabetSizeSymbol Context triple: [Reed–Solomon codes, alphabetSizeSymbol, q]
-
A.
alphabetSizeLatin
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
B.
alphabetType
Indicates the type or classification of an alphabet used by a writing system or language.
-
C.
alphabet
Indicates that one entity is an alphabet or set of symbols used for representing elements (such as characters or tokens) in relation to another entity.
-
D.
alphabetRange
Indicates that one entity specifies a contiguous range of letters in an alphabet that extends from the starting letter to the ending letter.
-
E.
characterSetSize
chosen
Indicates the total number of distinct characters contained in or allowed by a given character set.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f9a7d7d881909014fdf3746f981b |
completed | May 2, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 4:36 p.m.