Triple

T2045524
Position Surface form Disambiguated ID Type / Status
Subject Apple M2 Pro E45440 entity
Predicate powerEfficiency P27882 FINISHED
Object high 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: high | Statement: [Apple M2 Pro, powerEfficiency, high]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: powerEfficiency
Context triple: [Apple M2 Pro, powerEfficiency, high]
  • A. powerOptimizationFor
    Indicates a relationship where one entity is used to improve, manage, or optimize the power consumption or power efficiency of another entity.
  • B. energyEfficiencyFeature chosen
    Indicates that an entity has a design, technology, or characteristic specifically intended to reduce energy consumption or improve energy performance.
  • C. powerBudgetCharacteristic
    Indicates a relationship where an entity’s power consumption limits, allocations, or constraints are specified as a characteristic or parameter.
  • D. powerBudget
    Indicates the allocated or allowable amount of power that can be used or consumed by an entity or system within specified limits.
  • E. powerCharacteristic
    Indicates a relationship where one entity has a specific power-related property, capacity, or performance attribute characterized by the other entity.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abbc2c3f6c8190aff07097b2654e52 completed March 7, 2026, 5:48 a.m.
PD Predicate disambiguation batch_69abb7aa00d4819086d347d9a08f81a0 completed March 7, 2026, 5:29 a.m.
Created at: March 4, 2026, 7:39 p.m.