Triple

T2313358
Position Surface form Disambiguated ID Type / Status
Subject Process PEP E51007 entity
Predicate relatedTo P37 FINISHED
Object Python Enhancement Proposal E9267 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 Enhancement Proposal | Statement: [Process PEP, relatedTo, Python Enhancement Proposal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python Enhancement Proposal
Context triple: [Process PEP, relatedTo, Python Enhancement Proposal]
  • A. Python Enhancement Proposals chosen
    Python Enhancement Proposals (PEPs) are the formal design documents that propose, specify, and document new features, processes, and standards for the Python programming language.
  • B. PEP 622
    PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
  • C. PEP 13: Python Language Governance
    PEP 13: Python Language Governance is the Python Enhancement Proposal that defines the structure, responsibilities, and election process of the Python Steering Council, establishing the project's formal governance model.
  • D. Standards Track PEPs
    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.
  • E. PEP 572
    PEP 572 is the Python proposal that introduced the “walrus operator” (:=) for assignment expressions, allowing assignment within larger expressions.
  • 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_69aeb3bbea88819089f069be4d369692 completed March 9, 2026, 11:49 a.m.
Created at: March 4, 2026, 7:49 p.m.