Triple

T26409160
Position Surface form Disambiguated ID Type / Status
Subject GHASH E663911 entity
Predicate efficiencyReason P74576 FINISHED
Object uses binary field arithmetic amenable to parallelization 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: uses binary field arithmetic amenable to parallelization | Statement: [GHASH, efficiencyReason, uses binary field arithmetic amenable to parallelization]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: efficiencyReason
Context triple: [GHASH, efficiencyReason, uses binary field arithmetic amenable to parallelization]
  • A. reasonForIneffectiveness
    Indicates that one entity specifies the cause or explanation for why another entity is ineffective or fails to achieve its intended effect.
  • B. performanceImprovementReason chosen
    Indicates the reason or cause behind an observed or intended improvement in performance.
  • C. memoryEfficiencyReason
    Indicates that there is an explanation or cause for why something is efficient in its use of memory resources.
  • D. moreEfficientThan
    Indicates that one entity performs a task or uses resources with greater efficiency than another entity.
  • 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_69ee883931888190901be96d75ee23cc completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f610faa77081908956b6e8b5b1570c completed May 2, 2026, 2:58 p.m.
PD Predicate disambiguation batch_69f5f800fa9c8190aab0962669fde8ac completed May 2, 2026, 1:11 p.m.
Created at: April 26, 2026, 11:37 p.m.