Triple

T2313159
Position Surface form Disambiguated ID Type / Status
Subject PEP E51003 entity
Predicate documentedIn P309 FINISHED
Object PEP 1 – PEP Purpose and Guidelines
PEP 1 – PEP Purpose and Guidelines is the foundational Python Enhancement Proposal that defines the goals, structure, and workflow for all other PEPs in the Python development process.
 E255495 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 1 – PEP Purpose and Guidelines | Statement: [PEP, documentedIn, PEP 1 – PEP Purpose and Guidelines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PEP 1 – PEP Purpose and Guidelines
Context triple: [PEP, documentedIn, PEP 1 – PEP Purpose and Guidelines]
  • A. PEP 13
    PEP 13 is the Python Enhancement Proposal that defines the process and rules for selecting and operating the Python Steering Council, the core governance body of the Python project.
  • B. PEP 0
    PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
  • C. 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.
  • D. PEP 622
    PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
  • E. PEP 634
    PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced in Python 3.10.
  • 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 1 – PEP Purpose and Guidelines
Triple: [PEP, documentedIn, PEP 1 – PEP Purpose and Guidelines]
Generated description
PEP 1 – PEP Purpose and Guidelines is the foundational Python Enhancement Proposal that defines the goals, structure, and workflow for all other PEPs in the Python development process.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PEP 1 – PEP Purpose and Guidelines
Target entity description: PEP 1 – PEP Purpose and Guidelines is the foundational Python Enhancement Proposal that defines the goals, structure, and workflow for all other PEPs in the Python development process.
  • A. PEP 13
    PEP 13 is the Python Enhancement Proposal that defines the process and rules for selecting and operating the Python Steering Council, the core governance body of the Python project.
  • B. PEP 0
    PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
  • C. 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.
  • D. PEP 622
    PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
  • E. PEP 634
    PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced in Python 3.10.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61c1ef08190911d5f58c2e91189 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae895f5420819087b403e9772dce9a completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8af65eb88190b17d74e7411967cc completed March 9, 2026, 8:55 a.m.
NED2 Entity disambiguation (via description) batch_69ae8ba02cec8190917c0e17d3fedb0e completed March 9, 2026, 8:58 a.m.
Created at: March 4, 2026, 7:49 p.m.