Triple

T25677110
Position Surface form Disambiguated ID Type / Status
Subject Cantor–Zassenhaus algorithm E643836 entity
Predicate successProbability P7192 FINISHED
Object high for each random trial 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 for each random trial | Statement: [Cantor–Zassenhaus algorithm, successProbability, high for each random trial]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: successProbability
Context triple: [Cantor–Zassenhaus algorithm, successProbability, high for each random trial]
  • A. successRate chosen
    Indicates the proportion or frequency with which attempts at a given action or process result in a successful outcome.
  • B. successPeriod
    Indicates the time span during which a particular action, process, or entity is considered successful or yields successful outcomes.
  • C. successMetric
    Indicates the specific criterion or measure used to evaluate whether an action, process, or relationship has achieved its intended success.
  • D. relativeSuccess
    Indicates a comparison of how successful one entity is relative to another or to a defined benchmark.
  • E. hasFailureProbability
    Indicates that an entity is associated with a likelihood or chance that it will fail within a given context or 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_69e77e7f69808190ad27df1006f6037a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f69383222c81909d8baa04129d5c81 completed May 3, 2026, 12:14 a.m.
PD Predicate disambiguation batch_69f690eb1e948190aab41a89969519a5 completed May 3, 2026, 12:03 a.m.
Created at: April 21, 2026, 7:40 p.m.