Triple

T34674128
Position Surface form Disambiguated ID Type / Status
Subject Lax–Wendroff method E890451 entity
Predicate accuracyProperty P62233 FINISHED
Object second-order accurate for smooth solutions 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: second-order accurate for smooth solutions | Statement: [Lax–Wendroff method, accuracyProperty, second-order accurate for smooth solutions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: accuracyProperty
Context triple: [Lax–Wendroff method, accuracyProperty, second-order accurate for smooth solutions]
  • A. curacy
    Indicates that one entity serves in the role or position of a curate (assistant clergy) in relation to another entity, typically a parish or church.
  • B. accuracyDependsOn
    Indicates that the accuracy of one entity or process is contingent upon, or influenced by, another entity or factor.
  • C. hasAccuracy chosen
    Indicates that something possesses a specified level or measure of correctness, precision, or exactness in relation to a standard or reference.
  • D. accuracyCharacterization
    Indicates how precisely or reliably something is described, measured, or represented in relation to a given standard or truth.
  • E. precision
    Indicates the degree to which an action, measurement, or outcome is carried out with exactness, minimal deviation, and fine-grained accuracy.
  • 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_69f349d9c59481908b36baa0be093aea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72322256c8190afb14d73a2612b6f completed May 3, 2026, 10:27 a.m.
PD Predicate disambiguation batch_69f72157af108190880317a62e634bb0 completed May 3, 2026, 10:20 a.m.
Created at: May 1, 2026, 2:05 a.m.