Triple

T2313366
Position Surface form Disambiguated ID Type / Status
Subject Process PEP E51007 entity
Predicate contrastsWith P278 FINISHED
Object Standards Track PEP E258606 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: Standards Track PEP | Statement: [Process PEP, contrastsWith, Standards Track PEP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Standards Track PEP
Context triple: [Process PEP, contrastsWith, Standards Track PEP]
  • A. Standards Track PEPs chosen
    Standards Track PEPs are Python Enhancement Proposals that introduce or change core Python features, syntax, or standard library behavior and, once accepted, are intended to be implemented in the language.
  • B. PEP 1 – PEP Purpose and Guidelines
    PEP 1 – PEP Purpose and Guidelines is the foundational Python Enhancement Proposal that defines the goals, structure, and workflow for all other PEPs in the Python development process.
  • C. Standards Track
    Standards Track is the category of Python Enhancement Proposals that introduce or change core Python language features, standard libraries, or implementation details intended for widespread adoption.
  • D. 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.
  • E. PEP 622
    PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61c1ef08190911d5f58c2e91189 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea87427f08190b8353f74c5231a32 completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:49 p.m.