Triple

T2130606
Position Surface form Disambiguated ID Type / Status
Subject CPLD E46529 entity
Predicate hasDisadvantageComparedToFPGA P28754 FINISHED
Object lower logic density 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: lower logic density | Statement: [CPLD, hasDisadvantageComparedToFPGA, lower logic density]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDisadvantageComparedToFPGA
Context triple: [CPLD, hasDisadvantageComparedToFPGA, lower logic density]
  • A. hasDesignTradeoff chosen
    Indicates that one design choice involves compromises or conflicting benefits and drawbacks relative to other possible designs.
  • B. isLessEfficientThan
    Indicates that one entity performs a task or uses resources with lower efficiency compared to another entity.
  • C. gpuComputePerformance
    Indicates the level of processing capability a GPU can deliver for computational tasks, typically measured in operations per unit time.
  • D. hasMicrocontroller
    Indicates that an entity contains, includes, or is equipped with a microcontroller as one of its components.
  • E. neuralEnginePerformance
    Indicates the level or efficiency of processing capability provided by a neural engine in performing AI or machine-learning tasks.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb79f21881909ad8d1a09c1f29fd completed March 7, 2026, 5:45 a.m.
PD Predicate disambiguation batch_69abb7bd86cc8190938ef06c1ed6d969 completed March 7, 2026, 5:29 a.m.
Created at: March 4, 2026, 7:44 p.m.