Triple

T17521977
Position Surface form Disambiguated ID Type / Status
Subject packaging E426696 entity
Predicate supportsStandard P1587 FINISHED
Object PEP 566 NE NERFINISHED

How this triple was built (3 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: PEP 566 | Statement: [packaging, supportsStandard, PEP 566]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PEP 566
Context triple: [packaging, supportsStandard, PEP 566]
  • A. PEP 560
    PEP 560 is a Python Enhancement Proposal that optimizes and refines the implementation of typing and generic types in Python, improving performance and simplifying the internal mechanics of the typing module.
  • B. PEP 570
    PEP 570 is the Python Enhancement Proposal that introduced positional-only parameters to Python function definitions, formalizing a syntax for arguments that must be passed by position.
  • C. PEP 572
    PEP 572 is the Python proposal that introduced the “walrus operator” (:=) for assignment expressions, allowing assignment within larger expressions.
  • D. PEP 590
    PEP 590 is the Python Enhancement Proposal that introduced the "vectorcall" protocol to speed up and standardize function calls in CPython.
  • E. PEP 578
    PEP 578 is a Python enhancement proposal that introduces a security audit hook framework to help monitor and control runtime events in Python applications.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PEP 566
Target entity description: PEP 566 is a Python Enhancement Proposal that defines a standardized, extensible metadata format for Python packages to improve distribution and tooling interoperability.
  • A. PEP 560
    PEP 560 is a Python Enhancement Proposal that optimizes and refines the implementation of typing and generic types in Python, improving performance and simplifying the internal mechanics of the typing module.
  • B. PEP 570
    PEP 570 is the Python Enhancement Proposal that introduced positional-only parameters to Python function definitions, formalizing a syntax for arguments that must be passed by position.
  • C. PEP 572
    PEP 572 is the Python proposal that introduced the “walrus operator” (:=) for assignment expressions, allowing assignment within larger expressions.
  • D. PEP 590
    PEP 590 is the Python Enhancement Proposal that introduced the "vectorcall" protocol to speed up and standardize function calls in CPython.
  • E. PEP 578
    PEP 578 is a Python enhancement proposal that introduces a security audit hook framework to help monitor and control runtime events in Python applications.
  • F. None of above. chosen

Provenance (2 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d2f79881909556894728e255ab completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.