Triple

T2313136
Position Surface form Disambiguated ID Type / Status
Subject PEP E51003 entity
Predicate hasType P0 FINISHED
Object Informational PEP
An Informational PEP is a Python Enhancement Proposal that provides guidelines, general information, or recommendations to the Python community without specifying a new feature or process change.
 E51003 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: Informational PEP | Statement: [PEP, hasType, Informational PEP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Informational PEP
Context triple: [PEP, hasType, Informational PEP]
  • A. PEPs
    PEPs are formal design documents that propose and describe new features, processes, or changes for the Python programming language and its community.
  • B. PEP 1
    PEP 1 is the foundational Python Enhancement Proposal that defines the purpose, structure, and workflow for all other PEPs in the Python community process.
  • C. PEP 0
    PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
  • D. Pep
    Pep is the widely used nickname of Josep "Pep" Guardiola, the renowned Spanish football manager and former player.
  • E. Process PEP
    A Process PEP is a type of Python Enhancement Proposal that defines or changes procedures, workflows, and governance practices for the Python community rather than the language or its implementation.
  • 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: Informational PEP
Triple: [PEP, hasType, Informational PEP]
Generated description
An Informational PEP is a Python Enhancement Proposal that provides guidelines, general information, or recommendations to the Python community without specifying a new feature or process change.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Informational PEP
Target entity description: An Informational PEP is a Python Enhancement Proposal that provides guidelines, general information, or recommendations to the Python community without specifying a new feature or process change.
  • A. PEPs chosen
    PEPs are formal design documents that propose and describe new features, processes, or changes for the Python programming language and its community.
  • B. PEP 1
    PEP 1 is the foundational Python Enhancement Proposal that defines the purpose, structure, and workflow for all other PEPs in the Python community process.
  • C. PEP 0
    PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
  • D. Pep
    Pep is the widely used nickname of Josep "Pep" Guardiola, the renowned Spanish football manager and former player.
  • E. Process PEP
    A Process PEP is a type of Python Enhancement Proposal that defines or changes procedures, workflows, and governance practices for the Python community rather than the language or its implementation.
  • F. None of above.

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.