Triple

T1057157
Position Surface form Disambiguated ID Type / Status
Subject local existence and uniqueness theorem E22820 entity
Predicate isProvedBy P21917 FINISHED
Object Picard iteration
Picard iteration is a successive approximation method used to construct solutions to ordinary differential equations and establish their existence and uniqueness.
E121358 NE FINISHED

How this triple was built (5 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: Picard iteration | Statement: [local existence and uniqueness theorem, isProvedBy, Picard iteration]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Picard iteration
Context triple: [local existence and uniqueness theorem, isProvedBy, Picard iteration]
  • A. Gauss–Seidel method
    The Gauss–Seidel method is an iterative numerical technique used to solve systems of linear equations, particularly in large, sparse problems arising in scientific and engineering computations.
  • B. Euler’s method for numerical integration
    Euler’s method for numerical integration is a simple first-order numerical procedure used to approximate solutions to ordinary differential equations by stepping forward in small increments.
  • C. Crank–Nicolson scheme
    The Crank–Nicolson scheme is a finite difference method for numerically solving time-dependent partial differential equations, especially parabolic ones like the heat equation, known for its second-order accuracy and unconditional stability.
  • D. Aitken
    Aitken is a Scottish-origin surname notably borne by Max Aitken, 1st Baron Beaverbrook, a prominent Canadian-British newspaper magnate and politician.
  • E. Euler–Maruyama method
    The Euler–Maruyama method is a basic time-stepping scheme for numerically approximating solutions to stochastic differential equations, widely used in simulations of systems with noise such as Langevin dynamics.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Picard iteration
Triple: [local existence and uniqueness theorem, isProvedBy, Picard iteration]
Generated description
Picard iteration is a successive approximation method used to construct solutions to ordinary differential equations and establish their existence and uniqueness.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Picard iteration
Target entity description: Picard iteration is a successive approximation method used to construct solutions to ordinary differential equations and establish their existence and uniqueness.
  • A. Gauss–Seidel method
    The Gauss–Seidel method is an iterative numerical technique used to solve systems of linear equations, particularly in large, sparse problems arising in scientific and engineering computations.
  • B. Euler’s method for numerical integration
    Euler’s method for numerical integration is a simple first-order numerical procedure used to approximate solutions to ordinary differential equations by stepping forward in small increments.
  • C. Crank–Nicolson scheme
    The Crank–Nicolson scheme is a finite difference method for numerically solving time-dependent partial differential equations, especially parabolic ones like the heat equation, known for its second-order accuracy and unconditional stability.
  • D. Aitken
    Aitken is a Scottish-origin surname notably borne by Max Aitken, 1st Baron Beaverbrook, a prominent Canadian-British newspaper magnate and politician.
  • E. Euler–Maruyama method
    The Euler–Maruyama method is a basic time-stepping scheme for numerically approximating solutions to stochastic differential equations, widely used in simulations of systems with noise such as Langevin dynamics.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isProvedBy
Context triple: [local existence and uniqueness theorem, isProvedBy, Picard iteration]
  • A. attestedBy
    Indicates that the existence, occurrence, or validity of something is supported, confirmed, or documented by a specified source or authority.
  • B. proved chosen
    Indicates that one entity has demonstrated the truth or validity of another entity (such as a statement, theorem, or claim) through logical or evidential means.
  • C. believedBy
    Indicates that a particular proposition, statement, or entity is held to be true or accepted as real by a specified believer.
  • D. requiresProofOf
    Indicates that one entity must provide formal evidence or documentation to validate or authorize another entity.
  • E. attestedFrom
    Indicates the earliest point in time or source from which something is documented, recorded, or evidenced as existing or in use.
  • F. None of above.

Provenance (6 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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4ba6e35ac8190802341c31bda0e3b completed March 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bd110ac8190b66163de42bd3034 completed March 7, 2026, 2:53 p.m.
NEDg Description generation batch_69ac3d4b32348190883244f2b8af32a0 completed March 7, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_69ac3dbf5c70819084a942fc97a9b50f completed March 7, 2026, 3:01 p.m.
PD Predicate disambiguation batch_69a4b7340a048190807363f19d17a58f completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.