Triple

T7874857
Position Surface form Disambiguated ID Type / Status
Subject Layer Normalization E182824 entity
Predicate usesParameters P4452 FINISHED
Object learnable scale parameter gamma 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: learnable scale parameter gamma | Statement: [Layer Normalization, usesParameters, learnable scale parameter gamma]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesParameters
Context triple: [Layer Normalization, usesParameters, learnable scale parameter gamma]
  • A. hasParameter chosen
    Indicates that an entity is associated with a specific parameter that defines or constrains some aspect of its behavior, configuration, or characteristics.
  • B. usesMethods
    Indicates that one entity employs, applies, or relies on specific methods or techniques to perform an action or achieve a result.
  • C. usesProp
    Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
  • D. parameter
    Indicates that one entity serves as a parameter or argument that configures, constrains, or influences the behavior or outcome of another entity or process.
  • E. hasDimensionParameter
    Indicates that an entity is associated with a specific dimensional parameter (such as size, length, width, or height) that characterizes its measurable extent.
  • 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.