Triple
T364199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boltzmann machines |
E7922
|
entity |
| Predicate | hasLearningRule |
P2846
|
FINISHED |
| Object | stochastic gradient descent on log-likelihood |
—
|
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: stochastic gradient descent on log-likelihood | Statement: [Boltzmann machines, hasLearningRule, stochastic gradient descent on log-likelihood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLearningRule Context triple: [Boltzmann machines, hasLearningRule, stochastic gradient descent on log-likelihood]
-
A.
hasRule
chosen
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
-
B.
hasRulebook
Indicates that one entity possesses, is governed by, or is associated with a specific rulebook.
-
C.
usesRulesFrom
Indicates that one entity applies, follows, or is governed by the rules defined or provided by another entity.
-
D.
hasCognitiveComponent
Indicates that the related entity or process involves or depends on mental activities such as thinking, reasoning, perception, or understanding.
-
E.
isPracticedBy
Indicates that an activity, skill, or discipline is regularly performed or carried out by a particular 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebd1016481909b8ba3b047a47145 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.