Triple

T7897992
Position Surface form Disambiguated ID Type / Status
Subject Redis E183380 entity
Predicate persistenceMode P31904 FINISHED
Object in-memory with optional disk persistence 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: in-memory with optional disk persistence | Statement: [Redis, persistenceMode, in-memory with optional disk persistence]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: persistenceMode
Context triple: [Redis, persistenceMode, in-memory with optional disk persistence]
  • A. persistenceModel
    Indicates that one entity serves as the persistence representation or storage model used to save, load, or otherwise persist the state of another entity.
  • B. persistence
    Indicates a continued or repeated existence, occurrence, or effort of something over time despite potential changes or obstacles.
  • C. supportsPersistence chosen
    Indicates that one entity enables or provides the capability for another entity’s data or state to be stored and retained over time.
  • D. persistsAfter
    Indicates that one state, condition, or effect continues to exist after a specified event, time point, or other state has occurred or ended.
  • E. consistencyModel
    Indicates that one entity adheres to, implements, or is governed by a particular consistency model in its behavior or operations.
  • 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_69ca828d13088190b222be7aa9f9315c completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a296db8819084c620b12f77acb5 completed March 31, 2026, 3:06 a.m.
PD Predicate disambiguation batch_69cae92d94448190b4425bbfb64c658c completed March 30, 2026, 9:20 p.m.
Created at: March 30, 2026, 5:01 p.m.