Triple
T26253898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | extended binary Golay code |
E656668
|
entity |
| Predicate | numberOfWeight16Codewords |
P194799
|
FINISHED |
| Object | 759 |
—
|
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: 759 | Statement: [extended binary Golay code, numberOfWeight16Codewords, 759]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWeight16Codewords Context triple: [extended binary Golay code, numberOfWeight16Codewords, 759]
-
A.
numberOfCodewords
chosen
Indicates the total count of distinct codewords associated with a given coding scheme or code.
-
B.
hasCodewordsOfWeight
Indicates that one entity (typically a code) possesses codewords whose Hamming weight equals the specified value in the related entity.
-
C.
parityOfCodewords
Indicates that the relationship concerns whether the number of codewords (or bits within them) is even or odd, i.e., their parity.
-
D.
codeword
Indicates that one entity serves as a codeword or encoded representation used to convey, reference, or stand in for another entity within a coding or communication system.
-
E.
parityBits
Indicates that there is an association between data and the parity bits used to detect or correct errors in that data.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69fd91a5dad8819093eeeef527027890 |
completed | May 8, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69fd8f65fe9081908902500a3228d935 |
completed | May 8, 2026, 7:23 a.m. |
Created at: April 26, 2026, 9:08 p.m.