Triple

T4293681
Position Surface form Disambiguated ID Type / Status
Subject A3C E99656 entity
Predicate usesNeuralNetworks P55277 FINISHED
Object deep neural networks 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: deep neural networks | Statement: [A3C, usesNeuralNetworks, deep neural networks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesNeuralNetworks
Context triple: [A3C, usesNeuralNetworks, deep neural networks]
  • A. supportsNeuralNetworkAcceleration
    Indicates that one entity provides hardware or software capabilities that enhance the speed or efficiency of neural network computations for another entity.
  • B. NeuralEngineUseCases
    Indicates the various tasks, scenarios, or applications in which a neural engine is employed or leveraged.
  • C. integratesNeuralEngine
    Indicates that one entity incorporates or embeds a neural processing engine within its overall system or architecture.
  • D. neuralEnginePerformance
    Indicates the level or efficiency of processing capability provided by a neural engine in performing AI or machine-learning tasks.
  • E. neuralEngineType
    Indicates the specific kind or category of neural processing engine associated with or used by an entity.
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35082228081908504e3fd7c4ca1e8 completed March 12, 2026, 11:47 p.m.
PD Predicate disambiguation batch_69b347fe55a88190b77bab0c0f38e1aa completed March 12, 2026, 11:10 p.m.
PDg Predicate description generation batch_69b34e0606488190baadf469a1afc3c2 completed March 12, 2026, 11:36 p.m.
Created at: March 12, 2026, 11:08 p.m.