Triple

T25933336
Position Surface form Disambiguated ID Type / Status
Subject Intel Gaussian and Neural Accelerator 2.0 E653485 entity
Predicate powerEfficiencyGoal P15693 FINISHED
Object run AI tasks at minimal power 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: run AI tasks at minimal power | Statement: [Intel Gaussian and Neural Accelerator 2.0, powerEfficiencyGoal, run AI tasks at minimal power]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: powerEfficiencyGoal
Context triple: [Intel Gaussian and Neural Accelerator 2.0, powerEfficiencyGoal, run AI tasks at minimal power]
  • A. powerOptimizationFor chosen
    Indicates a relationship where one entity is used to improve, manage, or optimize the power consumption or power efficiency of another entity.
  • B. powerOptimized
    Indicates that an entity operates or is configured in a way that minimizes energy consumption or maximizes power efficiency.
  • C. energyUtilization
    Indicates how effectively an entity uses available energy to perform work or sustain its functions.
  • D. energyEfficiencyFeature
    Indicates that an entity has a design, technology, or characteristic specifically intended to reduce energy consumption or improve energy performance.
  • E. maximumEfficiency
    Indicates that an entity operates at its highest possible level of performance or productivity under given conditions.
  • 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_69e7ab3eb9b881909c1390690551f868 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f638d11c988190af7fd4572b08e038 completed May 2, 2026, 5:48 p.m.
PD Predicate disambiguation batch_69f63706b6008190993577193c85ff50 completed May 2, 2026, 5:40 p.m.
Created at: April 22, 2026, 8:37 a.m.