Triple

T12597458
Position Surface form Disambiguated ID Type / Status
Subject classical fourth-order Runge–Kutta method E300768 entity
Predicate definesK2As P105621 FINISHED
Object k2 = f(t_n + h/2, y_n + h k1 / 2) 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: k2 = f(t_n + h/2, y_n + h k1 / 2) | Statement: [classical fourth-order Runge–Kutta method, definesK2As, k2 = f(t_n + h/2, y_n + h k1 / 2)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: definesK2As
Context triple: [classical fourth-order Runge–Kutta method, definesK2As, k2 = f(t_n + h/2, y_n + h k1 / 2)]
  • A. secondDefinition
    Indicates that one entity serves as an alternative or secondary definition or meaning for another entity.
  • B. definesSystemAs
    Indicates that one entity explicitly specifies or establishes another entity as the system to be used, referenced, or treated as authoritative.
  • C. definitionType
    Indicates the specific kind or category of definition that characterizes how one entity is defined in relation to another.
  • D. definesClassification
    Indicates that one entity specifies or establishes the classification or category to which another entity belongs.
  • E. definesFunctioningOf
    Indicates that one entity specifies or determines how another entity operates or functions.
  • F. None of above. chosen

Provenance (4 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954e6e20481908bca684c4b497c48 completed April 10, 2026, 7:52 p.m.
PD Predicate disambiguation batch_69d95416cbd88190b2c65196162349bc completed April 10, 2026, 7:48 p.m.
PDg Predicate description generation batch_69d954e351f88190869220d46e0ce282 completed April 10, 2026, 7:52 p.m.
Created at: April 9, 2026, 5:08 p.m.