Triple
T7874711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam optimizer |
E182821
|
entity |
| Predicate | defaultEpsilon |
P79505
|
FINISHED |
| Object | 1e-8 |
—
|
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: 1e-8 | Statement: [Adam optimizer, defaultEpsilon, 1e-8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defaultEpsilon Context triple: [Adam optimizer, defaultEpsilon, 1e-8]
-
A.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
B.
typicalDefaultLearningRate
Indicates the standard or commonly used learning rate value typically applied by default in a learning or optimization process.
-
C.
defaultParameterSet
Indicates that a particular set of parameters is designated as the standard or fallback configuration to be used when no other specific parameter set is provided.
-
D.
offsetStandardApprox
Indicates that one value serves as an approximate standard or baseline from which another value is offset or deviates.
-
E.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
- F. None of above. chosen
Provenance (4 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a961188190b2f12f8fe5d66641 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:56 p.m.