Triple

T10818152
Position Surface form Disambiguated ID Type / Status
Subject PEP 635 E255288 entity
Predicate title P38 FINISHED
Object Structural Pattern Matching: Motivation and Rationale E253899 NE 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: Structural Pattern Matching: Motivation and Rationale | Statement: [PEP 635, title, Structural Pattern Matching: Motivation and Rationale]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Structural Pattern Matching: Motivation and Rationale
Context triple: [PEP 635, title, Structural Pattern Matching: Motivation and Rationale]
  • A. Structural Pattern Matching chosen
    Structural Pattern Matching is a Python language feature, introduced via PEP 622, that enables powerful, declarative matching of complex data structures using a `match`/`case` syntax.
  • B. Analysis Patterns: Reusable Object Models
    Analysis Patterns: Reusable Object Models is a software engineering book by Martin Fowler that presents recurring object-oriented design solutions for modeling complex business domains.
  • C. Hindley–Milner type system
    The Hindley–Milner type system is a classical polymorphic type system used in many functional programming languages, notable for enabling type inference without explicit type annotations.
  • D. Domain-Specific Languages
    Domain-Specific Languages is a technical book by Martin Fowler that explores the design, implementation, and practical use of specialized programming languages tailored to specific problem domains.
  • E. Practical Aspects of Declarative Languages
    Practical Aspects of Declarative Languages is an academic conference focused on the practical implementation, application, and evaluation of declarative programming languages and related technologies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7344866f88190be4addb7c8020fce completed April 9, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69de855799748190b51745a198daa8d0 completed April 14, 2026, 6:20 p.m.
Created at: April 8, 2026, 9:18 p.m.