Triple

T10763900
Position Surface form Disambiguated ID Type / Status
Subject Python 3.10 E253903 entity
Predicate implementsPEP P43638 FINISHED
Object PEP 626
PEP 626 is a Python Enhancement Proposal that precisely defines how Python should map executed bytecode instructions to source code lines, improving debugging, coverage measurement, and tooling accuracy.
E909747 NE FINISHED

How this triple was built (4 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 626 | Statement: [Python 3.10, implementsPEP, PEP 626]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PEP 626
Context triple: [Python 3.10, implementsPEP, PEP 626]
  • A. PEP 636
    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.
  • 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 624
    PEP 624 is a Python Enhancement Proposal that specifies the removal of the Py_UNICODE encoder APIs from the CPython C API to streamline and modernize Unicode handling in Python.
  • D. PEP 634
    PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: PEP 626
Triple: [Python 3.10, implementsPEP, PEP 626]
Generated description
PEP 626 is a Python Enhancement Proposal that precisely defines how Python should map executed bytecode instructions to source code lines, improving debugging, coverage measurement, and tooling accuracy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PEP 626
Target entity description: PEP 626 is a Python Enhancement Proposal that precisely defines how Python should map executed bytecode instructions to source code lines, improving debugging, coverage measurement, and tooling accuracy.
  • A. PEP 636
    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.
  • 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 624
    PEP 624 is a Python Enhancement Proposal that specifies the removal of the Py_UNICODE encoder APIs from the CPython C API to streamline and modernize Unicode handling in Python.
  • D. PEP 634
    PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching 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. chosen

Provenance (5 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d731a504948190943f0e27c0d891ed completed April 9, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69e482f327e48190ad087c232fd05609 completed April 19, 2026, 7:23 a.m.
NEDg Description generation batch_69e48715bd2081908774d325db2b6dd5 completed April 19, 2026, 7:41 a.m.
NED2 Entity disambiguation (via description) batch_69e4886c0da881909105b3a45e786ce9 completed April 19, 2026, 7:46 a.m.
Created at: April 8, 2026, 9:16 p.m.