Triple
T10992288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadamard fractional integral |
E259779
|
entity |
| Predicate | usesKernelType |
P5103
|
FINISHED |
| Object | logarithmic kernel |
—
|
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: logarithmic kernel | Statement: [Hadamard fractional integral, usesKernelType, logarithmic kernel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesKernelType Context triple: [Hadamard fractional integral, usesKernelType, logarithmic kernel]
-
A.
hasKernelType
Indicates that an entity possesses or is associated with a specific type or classification of kernel.
-
B.
primaryKernelType
Indicates that one entity is the main or default kernel type associated with another entity.
-
C.
hasKernel
Indicates that one entity functions as the kernel (core or central component) of another entity.
-
D.
kernelType
chosen
Indicates the specific kind or category of kernel associated with or used by an entity.
-
E.
usesServerType
Indicates that an entity operates on, is hosted by, or otherwise relies on a specific type or category of server.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d32f9081909def643571499521 |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.