Triple

T17557263
Position Surface form Disambiguated ID Type / Status
Subject PEP 420 E427619 entity
Predicate relatedTo P37 FINISHED
Object PEP 382
PEP 382 is a Python Enhancement Proposal that originally specified a mechanism for namespace packages using explicit “.pkg” files, an approach later superseded by the implicit namespace package model of PEP 420.
 E1279211 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 382 | Statement: [PEP 420, relatedTo, PEP 382]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PEP 382
Context triple: [PEP 420, relatedTo, PEP 382]
  • A. PEP 328
    PEP 328 is a Python Enhancement Proposal that introduced and standardized the syntax and semantics for absolute and relative imports in Python.
  • B. PEP 386
    PEP 386 is a Python Enhancement Proposal that originally specified a version identification scheme for Python software distributions before being superseded by PEP 440.
  • C. PEP 302
    PEP 302 is a Python Enhancement Proposal that defines the import hook mechanism, enabling customization and extension of Python’s module import system.
  • D. PEP 483
    PEP 483 is a Python Enhancement Proposal that lays out the theoretical foundations and design principles for Python’s type hinting and generic types system.
  • E. PEP 345
    PEP 345 is a Python Enhancement Proposal that defines the metadata format for Python software packages, including standardized fields used in package distribution.
  • 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 382
Triple: [PEP 420, relatedTo, PEP 382]
Generated description
PEP 382 is a Python Enhancement Proposal that originally specified a mechanism for namespace packages using explicit “.pkg” files, an approach later superseded by the implicit namespace package model of PEP 420.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PEP 382
Target entity description: PEP 382 is a Python Enhancement Proposal that originally specified a mechanism for namespace packages using explicit “.pkg” files, an approach later superseded by the implicit namespace package model of PEP 420.
  • A. PEP 328
    PEP 328 is a Python Enhancement Proposal that introduced and standardized the syntax and semantics for absolute and relative imports in Python.
  • B. PEP 386
    PEP 386 is a Python Enhancement Proposal that originally specified a version identification scheme for Python software distributions before being superseded by PEP 440.
  • C. PEP 302
    PEP 302 is a Python Enhancement Proposal that defines the import hook mechanism, enabling customization and extension of Python’s module import system.
  • D. PEP 483
    PEP 483 is a Python Enhancement Proposal that lays out the theoretical foundations and design principles for Python’s type hinting and generic types system.
  • E. PEP 345
    PEP 345 is a Python Enhancement Proposal that defines the metadata format for Python software packages, including standardized fields used in package distribution.
  • 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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4562413d08190acaa5272046d3626 completed April 19, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a020a8767a08190bcdc8193b2b44127 completed May 11, 2026, 4:57 p.m.
NEDg Description generation batch_6a020c10d1bc81909b0f04337df36be8 completed May 11, 2026, 5:04 p.m.
NED2 Entity disambiguation (via description) batch_6a020cefce4c8190a92f543533e4b801 completed May 11, 2026, 5:08 p.m.
Created at: April 10, 2026, 5:50 a.m.