Triple
T17676450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bidiagonal matrix |
E440653
|
entity |
| Predicate | hasNonzeroEntriesOn |
P18283
|
FINISHED |
| Object | Main diagonal |
—
|
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: Main diagonal | Statement: [Bidiagonal matrix, hasNonzeroEntriesOn, Main diagonal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonzeroEntriesOn Context triple: [Bidiagonal matrix, hasNonzeroEntriesOn, Main diagonal]
-
A.
isNonzeroFor
Indicates that a given value, function, or quantity is not equal to zero under specified conditions or for specified inputs.
-
B.
hasOffDiagonalEntries
Indicates that a matrix or similar structured object contains at least one non-zero element outside its main diagonal.
-
C.
hasEntryOn
chosen
Indicates that one entity contains or includes an entry, record, or listing about another entity.
-
D.
isNonZeroBecause
Indicates that a value is non-zero specifically due to the stated cause, reason, or contributing factor.
-
E.
hasSubjectEntriesIn
Indicates that a subject is recorded or represented within specific entries of a collection, dataset, or catalog.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6d9ab88190ab0e25eac8b0101c |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:01 a.m.