Triple
T19050707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirichlet kernel |
E466248
|
entity |
| Predicate | L1NormBehavior |
P6112
|
FINISHED |
| Object | L^1 norm grows like O(log n) |
—
|
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: L^1 norm grows like O(log n) | Statement: [Dirichlet kernel, L1NormBehavior, L^1 norm grows like O(log n)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: L1NormBehavior Context triple: [Dirichlet kernel, L1NormBehavior, L^1 norm grows like O(log n)]
-
A.
normType
Indicates the specific category or classification of a norm that governs or constrains an entity or situation.
-
B.
normIs
Indicates that something conforms to, or is characterized by, a particular standard, rule, or norm.
-
C.
minimalNorm
Indicates that among a set of possible values or solutions, this one has the smallest norm (magnitude) according to a specified norm measure.
-
D.
limitBehavior
chosen
Indicates how an entity behaves or changes as it approaches a specified limit or boundary condition.
-
E.
regularizationControlledBy
Indicates that the regularization applied in a process, model, or system is governed, adjusted, or determined by a specific controlling factor or mechanism.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc02597c8190b39fd2c7b7e42258 |
completed | April 20, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.