Triple

T10763906
Position Surface form Disambiguated ID Type / Status
Subject Python 3.10 E253903 entity
Predicate implementsPEP P43638 FINISHED
Object PEP 649
PEP 649 is a Python enhancement proposal that introduces a new, lazy evaluation scheme for type annotations to improve performance and forward-reference handling.
E918446 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 649 | Statement: [Python 3.10, implementsPEP, PEP 649]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PEP 649
Context triple: [Python 3.10, implementsPEP, PEP 649]
  • A. PEP 644
    PEP 644 is the Python Enhancement Proposal that mandates OpenSSL 1.1.1 or newer as the minimum supported version for Python’s standard ssl module, aligning Python’s security features with modern TLS capabilities.
  • B. PEP 634
    PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced 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 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 647
    PEP 647 is the Python Enhancement Proposal that introduces "user-defined type guards," enabling more precise static type narrowing in Python code.
  • 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 649
Triple: [Python 3.10, implementsPEP, PEP 649]
Generated description
PEP 649 is a Python enhancement proposal that introduces a new, lazy evaluation scheme for type annotations to improve performance and forward-reference handling.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PEP 649
Target entity description: PEP 649 is a Python enhancement proposal that introduces a new, lazy evaluation scheme for type annotations to improve performance and forward-reference handling.
  • A. PEP 644
    PEP 644 is the Python Enhancement Proposal that mandates OpenSSL 1.1.1 or newer as the minimum supported version for Python’s standard ssl module, aligning Python’s security features with modern TLS capabilities.
  • B. PEP 634
    PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced 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 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 647
    PEP 647 is the Python Enhancement Proposal that introduces "user-defined type guards," enabling more precise static type narrowing in Python code.
  • 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_69e5252da538819091f63ce34709b3b7 completed April 19, 2026, 6:55 p.m.
NEDg Description generation batch_69e52a78951c8190923711067cf4e7e5 completed April 19, 2026, 7:18 p.m.
NED2 Entity disambiguation (via description) batch_69e5319b6ef0819096debabfb6ffbe70 completed April 19, 2026, 7:48 p.m.
Created at: April 8, 2026, 9:16 p.m.