Triple

T10818176
Position Surface form Disambiguated ID Type / Status
Subject PEP 635 E255288 entity
Predicate partOf P40 FINISHED
Object Python 3.10 pattern matching PEP series E257816 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: Python 3.10 pattern matching PEP series | Statement: [PEP 635, partOf, Python 3.10 pattern matching PEP series]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Python 3.10 pattern matching PEP series
Context triple: [PEP 635, partOf, Python 3.10 pattern matching PEP series]
  • A. Structural Pattern Matching
    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. Python 3.10
    Python 3.10 is a major release of the Python programming language that introduced structural pattern matching and various syntax and performance improvements.
  • C. PEP 572
    PEP 572 is the Python proposal that introduced the “walrus operator” (:=) for assignment expressions, allowing assignment within larger expressions.
  • D. PEP 636 chosen
    PEP 636 is a Python Enhancement Proposal that serves as a tutorial-style guide to the structural pattern matching feature introduced in Python 3.10.
  • E. PEP 695
    PEP 695 is a Python Enhancement Proposal that introduces a new, more concise syntax for type parameter declarations to improve the language’s support for generics and static typing.
  • 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.