Triple
T591907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LeNet |
E17289
|
entity |
| Predicate | regularization |
P16020
|
FINISHED |
| Object | weight decay |
—
|
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: weight decay | Statement: [LeNet, regularization, weight decay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regularization Context triple: [LeNet, regularization, weight decay]
-
A.
primaryRegulator
Indicates that one entity serves as the main controlling or governing authority over another entity or process.
-
B.
regulatesUse
Indicates that one entity controls, governs, or sets rules for how another entity may be used.
-
C.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
-
D.
regulatesWith
Indicates that one entity controls, modulates, or influences the activity, state, or behavior of another entity through some regulatory mechanism or interaction.
-
E.
normType
Indicates the specific category or classification of a norm that governs or constrains an entity or situation.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bbaf53081908eed240bed09f63b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cc13988190892ca10bd7ae9f09 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985ada988190aaea628a9b55bca4 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.