Triple

T32669321
Position Surface form Disambiguated ID Type / Status
Subject ELBO E835245 entity
Predicate regularizationTermOften P56045 FINISHED
Object KL(q(z|x) || p(z)) 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: KL(q(z|x) || p(z)) | Statement: [ELBO, regularizationTermOften, KL(q(z|x) || p(z))]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regularizationTermOften
Context triple: [ELBO, regularizationTermOften, KL(q(z|x) || p(z))]
  • A. regularization
    Indicates the application of a constraint or penalty to a model or function to prevent overfitting and encourage simpler, more generalizable behavior.
  • B. regularizationControlledBy
    Indicates that the regularization applied in a process, model, or system is governed, adjusted, or determined by a specific controlling factor or mechanism.
  • C. regularityAssumption
    Indicates that a relationship or process is assumed to behave in a consistent, well-behaved manner (e.g., continuity, smoothness, or stability) so that certain analyses or inferences are valid.
  • D. typicalTerm chosen
    Indicates that something is a standard, representative, or characteristic term typically associated with a given concept or context.
  • E. hasRegularity
    Indicates that one entity exhibits a consistent, recurring pattern or uniform behavior with respect to another entity or over time.
  • 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_69f349303ccc8190a70d0f6e8a21d3fb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69fd2a215d6c8190a1a428ccaee603f1 completed May 8, 2026, 12:11 a.m.
PD Predicate disambiguation batch_69fd28ef19688190bb8370f2812a43e7 completed May 8, 2026, 12:06 a.m.
Created at: May 1, 2026, 1:08 a.m.