Triple

T17022657
Position Surface form Disambiguated ID Type / Status
Subject Princeton architecture E412983 entity
Predicate performanceImplication P20527 FINISHED
Object cache hierarchies used to mitigate bottleneck 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: cache hierarchies used to mitigate bottleneck | Statement: [Princeton architecture, performanceImplication, cache hierarchies used to mitigate bottleneck]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: performanceImplication
Context triple: [Princeton architecture, performanceImplication, cache hierarchies used to mitigate bottleneck]
  • A. impactOnPerformance chosen
    Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
  • B. performance
    Indicates that one entity’s effectiveness, quality, or success in carrying out a task, function, or role is being evaluated or characterized in relation to some standard or expectation.
  • C. performanceDependsOn
    Indicates that the quality or outcome of one entity’s performance is contingent upon or influenced by another specified factor or entity.
  • D. performanceFeature
    Indicates that an entity possesses a characteristic, capability, or attribute specifically related to its performance or operational effectiveness.
  • E. encodingImpact
    Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d1d2e48190bbcba129247c6c2e completed April 18, 2026, 7:04 p.m.
PD Predicate disambiguation batch_69e35d5be7f48190af9db67a1e23850f completed April 18, 2026, 10:30 a.m.
Created at: April 10, 2026, 5:33 a.m.