Triple

T17561512
Position Surface form Disambiguated ID Type / Status
Subject Firestore E427703 entity
Predicate dataConsistencyModel P55185 FINISHED
Object strong consistency for single documents 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: strong consistency for single documents | Statement: [Firestore, dataConsistencyModel, strong consistency for single documents]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: dataConsistencyModel
Context triple: [Firestore, dataConsistencyModel, strong consistency for single documents]
  • A. consistencyModel chosen
    Indicates that one entity adheres to, implements, or is governed by a particular consistency model in its behavior or operations.
  • B. hasConsistency
    Indicates that one entity maintains a stable, uniform, or coherent state, behavior, or set of properties in relation to another entity or over time.
  • C. memoryModel
    Indicates a relationship where an entity serves as or uses a specific model or framework for representing, organizing, or managing memory.
  • D. durabilityModel
    Indicates a relationship where an entity is associated with a specific model or method used to estimate or characterize its durability over time or under certain conditions.
  • E. concurrentModel
    Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
  • 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e456274c888190ac80402e391674dd completed April 19, 2026, 4:12 a.m.
PD Predicate disambiguation batch_69e3b4fd7d048190b54ee4c6155612a5 completed April 18, 2026, 4:44 p.m.
Created at: April 10, 2026, 5:50 a.m.