Provisional PEPs
E255501
Provisional PEPs are a category of Python Enhancement Proposals that introduce features or changes on a trial basis, allowing them to be tested and refined before being fully accepted or rejected.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Provisional PEPs canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2313328 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Provisional PEPs Context triple: [PEP 0, hasSection, Provisional PEPs]
-
A.
Presidential Elections Committee (eligibility vetting)
The Presidential Elections Committee (eligibility vetting) is the body in Singapore responsible for assessing and certifying whether prospective presidential candidates meet the constitutional and statutory eligibility requirements to stand for election.
-
B.
Panel of Experts
The Panel of Experts is a group of specialists appointed by the United Nations to monitor, investigate, and report on the implementation and impact of specific UN sanctions regimes.
-
C.
Denied Persons List
The Denied Persons List is a U.S. government trade-restriction list identifying individuals and entities prohibited from participating in export-related activities.
-
D.
Assembly of Experts
The Assembly of Experts is a powerful Iranian clerical body responsible for selecting, overseeing, and theoretically dismissing the country’s Supreme Leader.
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E.
Permanent Bureau
The Permanent Bureau was the central administrative body responsible for coordinating and managing the ongoing work of the International Institute of Agriculture.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Provisional PEPs Target entity description: Provisional PEPs are a category of Python Enhancement Proposals that introduce features or changes on a trial basis, allowing them to be tested and refined before being fully accepted or rejected.
-
A.
Presidential Elections Committee (eligibility vetting)
The Presidential Elections Committee (eligibility vetting) is the body in Singapore responsible for assessing and certifying whether prospective presidential candidates meet the constitutional and statutory eligibility requirements to stand for election.
-
B.
Panel of Experts
The Panel of Experts is a group of specialists appointed by the United Nations to monitor, investigate, and report on the implementation and impact of specific UN sanctions regimes.
-
C.
Denied Persons List
The Denied Persons List is a U.S. government trade-restriction list identifying individuals and entities prohibited from participating in export-related activities.
-
D.
Assembly of Experts
The Assembly of Experts is a powerful Iranian clerical body responsible for selecting, overseeing, and theoretically dismissing the country’s Supreme Leader.
-
E.
Permanent Bureau
The Permanent Bureau was the central administrative body responsible for coordinating and managing the ongoing work of the International Institute of Agriculture.
- F. None of above. chosen
Statements (41)
| Predicate | Object |
|---|---|
| instanceOf |
PEP status category
ⓘ
Python language process concept ⓘ |
| affects |
Python version release notes
ⓘ
stability guarantees of affected APIs ⓘ |
| aimsTo | balance innovation with stability in Python ⓘ |
| appliesTo |
Python language features
ⓘ
Python standard library ⓘ |
| clarifiedIn | PEP documentation about provisional APIs ⓘ |
| distinguishedFrom | fully stable, guaranteed APIs ⓘ |
| documentedIn |
PEP index
ⓘ
individual PEP documents ⓘ |
| evaluatedBy |
Python core developers
ⓘ
wider Python community feedback ⓘ |
| governedBy |
PEP process guidelines
ⓘ
Python core developer decisions ⓘ |
| hasCharacteristic |
APIs may change without normal deprecation process
ⓘ
documented as provisional in Python documentation ⓘ may be promoted to fully accepted ⓘ may be rejected after trial ⓘ may be reverted ⓘ subject to change ⓘ temporary acceptance status ⓘ |
| hasPurpose |
evaluating feature viability
ⓘ
gathering real‑world feedback ⓘ reducing risk of permanent design mistakes ⓘ refining proposed features ⓘ trial introduction of features ⓘ |
| hasTemporalScope | limited to one or more Python release cycles ⓘ |
| partOf |
Python Enhancement Proposal process
ⓘ
linked to:
Python Enhancement Proposals
|
| relatedTo |
Accepted PEPs
ⓘ
Deferred PEPs ⓘ
linked to:
PEPs
Draft PEPs ⓘ Final PEPs ⓘ PEP status field ⓘ Rejected PEPs ⓘ |
| requires | explicit documentation of provisional status ⓘ |
| resultsIn | either full acceptance or rejection after evaluation ⓘ |
| usedFor |
introducing experimental APIs
ⓘ
introducing experimental standard library modules ⓘ testing new language or library designs in practice ⓘ |
| usedIn |
CPython development
ⓘ
linked to:
Python reference implementation (CPython)
|
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Provisional PEPs Description of subject: Provisional PEPs are a category of Python Enhancement Proposals that introduce features or changes on a trial basis, allowing them to be tested and refined before being fully accepted or rejected.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.