Triple

T645542
Position Surface form Disambiguated ID Type / Status
Subject A fast learning algorithm for deep belief nets E11232 entity
Predicate architectureProperty P16907 FINISHED
Object multiple layers of latent variables 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: multiple layers of latent variables | Statement: [A fast learning algorithm for deep belief nets, architectureProperty, multiple layers of latent variables]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: architectureProperty
Context triple: [A fast learning algorithm for deep belief nets, architectureProperty, multiple layers of latent variables]
  • A. architectureType
    Indicates the specific style or category of architecture that characterizes or defines an entity.
  • B. buildingType
    Indicates the specific category or function that characterizes what kind of building something is.
  • C. builtProperty
    Indicates that a constructed structure or building has been created on, or is associated with, a particular property or piece of land.
  • D. building
    Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
  • E. roofFeature
    Indicates that one entity is a feature, element, or characteristic that is part of or associated with a roof.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f19f9a08190b0bf6e19b32427ff completed March 1, 2026, 8:18 p.m.
PD Predicate disambiguation batch_69a49d0a0ab481909871461418a00be7 completed March 1, 2026, 8:09 p.m.
PDg Predicate description generation batch_69a49dc0e6a08190b81d82a6f2571c41 completed March 1, 2026, 8:12 p.m.
Created at: March 1, 2026, 7:36 p.m.