Triple
T7874701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam optimizer |
E182821
|
entity |
| Predicate | updateRuleType |
P32462
|
FINISHED |
| Object | adaptive learning rate |
—
|
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: adaptive learning rate | Statement: [Adam optimizer, updateRuleType, adaptive learning rate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: updateRuleType Context triple: [Adam optimizer, updateRuleType, adaptive learning rate]
-
A.
typicalRuleModification
Indicates a change made to a standard or default rule, adjusting how that rule normally applies or operates.
-
B.
changeType
Indicates the specific kind or category of modification that has occurred to an entity or relationship.
-
C.
updatesSpecificationOf
Indicates that one entity revises, modifies, or replaces the existing specification of another entity.
-
D.
typeOfRule
chosen
Indicates that one rule is classified as a specific kind or category of another, more general rule.
-
E.
mutationType
Indicates the specific kind or category of genetic alteration that has occurred in an entity.
- 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.