Triple

T11215921
Position Surface form Disambiguated ID Type / Status
Subject Python generic class definitions E265439 entity
Predicate formalizedIn P6279 FINISHED
Object 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.
 E935160 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 560 | Statement: [Python generic class definitions, formalizedIn, PEP 560]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PEP 560
Context triple: [Python generic class definitions, formalizedIn, PEP 560]
  • A. PEP 590
    PEP 590 is the Python Enhancement Proposal that introduced the "vectorcall" protocol to speed up and standardize function calls in CPython.
  • B. PEP 552
    PEP 552 is a Python Enhancement Proposal that introduced deterministic, hash-based .pyc files to improve reproducibility and caching behavior in Python.
  • C. 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.
  • D. 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.
  • 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.
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 560
Triple: [Python generic class definitions, formalizedIn, PEP 560]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PEP 560
Target entity description: 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.
  • A. PEP 590
    PEP 590 is the Python Enhancement Proposal that introduced the "vectorcall" protocol to speed up and standardize function calls in CPython.
  • B. PEP 552
    PEP 552 is a Python Enhancement Proposal that introduced deterministic, hash-based .pyc files to improve reproducibility and caching behavior in Python.
  • C. 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.
  • D. 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.
  • 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 (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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8e8eef48190932a85784ce15c86 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e712e6288481908071e248a50209e0 completed April 21, 2026, 6:02 a.m.
NEDg Description generation batch_69e720f4015c81909ba7973c3e781985 completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e75a7a04c88190bb8f3dd3f3e435ef completed April 21, 2026, 11:07 a.m.
Created at: April 8, 2026, 9:30 p.m.