Triple
T7874708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam optimizer |
E182821
|
entity |
| Predicate | defaultLearningRate |
P68349
|
FINISHED |
| Object | 0.001 |
—
|
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: 0.001 | Statement: [Adam optimizer, defaultLearningRate, 0.001]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defaultLearningRate Context triple: [Adam optimizer, defaultLearningRate, 0.001]
-
A.
typicalDefaultLearningRate
chosen
Indicates the standard or commonly used learning rate value typically applied by default in a learning or optimization process.
-
B.
learn
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
C.
initialGuess
Indicates the starting value or preliminary estimate chosen before an iterative or refinement process begins.
-
D.
acceleratingGradient
Indicates that a process, change, or effect is increasing in rate over time, becoming progressively faster or more intense.
-
E.
trainingMethod
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
- 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_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. |
Created at: March 30, 2026, 4:56 p.m.