Triple

T10763907
Position Surface form Disambiguated ID Type / Status
Subject Python 3.10 E253903 entity
Predicate implementsPEP P43638 FINISHED
Object PEP 657
PEP 657 is a Python enhancement proposal that improves error reporting by adding fine-grained location information (such as per-expression line and column data) to tracebacks.
E919523 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 657 | Statement: [Python 3.10, implementsPEP, PEP 657]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PEP 657
Context triple: [Python 3.10, implementsPEP, PEP 657]
  • A. 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.
  • 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 647
    PEP 647 is the Python Enhancement Proposal that introduces "user-defined type guards," enabling more precise static type narrowing in Python code.
  • D. 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.
  • E. 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.
  • 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 657
Triple: [Python 3.10, implementsPEP, PEP 657]
Generated description
PEP 657 is a Python enhancement proposal that improves error reporting by adding fine-grained location information (such as per-expression line and column data) to tracebacks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PEP 657
Target entity description: PEP 657 is a Python enhancement proposal that improves error reporting by adding fine-grained location information (such as per-expression line and column data) to tracebacks.
  • A. 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.
  • 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 647
    PEP 647 is the Python Enhancement Proposal that introduces "user-defined type guards," enabling more precise static type narrowing in Python code.
  • D. 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.
  • E. 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.
  • 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_69e54263e930819099524917506c7eab completed April 19, 2026, 9 p.m.
NEDg Description generation batch_69e545ad9840819096cb11f1d427ea38 completed April 19, 2026, 9:14 p.m.
NED2 Entity disambiguation (via description) batch_69e548c50aac81909f94ac2f35a29f41 completed April 19, 2026, 9:27 p.m.
Created at: April 8, 2026, 9:16 p.m.