Triple

T18051059
Position Surface form Disambiguated ID Type / Status
Subject dataclasses E431926 entity
Predicate definedIn P775 FINISHED
Object PEP 557
PEP 557 is the Python Enhancement Proposal that introduced dataclasses, a standard way to create classes for storing data with less boilerplate code.
E1305679 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 557 | Statement: [dataclasses, definedIn, PEP 557]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PEP 557
Context triple: [dataclasses, definedIn, PEP 557]
  • A. PEP 552
    PEP 552 is a Python Enhancement Proposal that introduced deterministic, hash-based .pyc files to improve reproducibility and caching behavior in Python.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. PEP 544
    PEP 544 is a Python Enhancement Proposal that introduces structural subtyping via typing.Protocol, enabling static type checkers to support interface-like behavior based on object capabilities rather than inheritance.
  • 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 557
Triple: [dataclasses, definedIn, PEP 557]
Generated description
PEP 557 is the Python Enhancement Proposal that introduced dataclasses, a standard way to create classes for storing data with less boilerplate code.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PEP 557
Target entity description: PEP 557 is the Python Enhancement Proposal that introduced dataclasses, a standard way to create classes for storing data with less boilerplate code.
  • A. PEP 552
    PEP 552 is a Python Enhancement Proposal that introduced deterministic, hash-based .pyc files to improve reproducibility and caching behavior in Python.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. PEP 544
    PEP 544 is a Python Enhancement Proposal that introduces structural subtyping via typing.Protocol, enabling static type checkers to support interface-like behavior based on object capabilities rather than inheritance.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bff57ea08190a30a87993f7d3299 completed April 19, 2026, 11:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a035d8448508190b664a48cbaf3d150 completed May 12, 2026, 5:04 p.m.
NEDg Description generation batch_6a036ce6f2908190b8f846e23d5bf44b completed May 12, 2026, 6:09 p.m.
NED2 Entity disambiguation (via description) batch_6a036d55af7081909540768983963e8a completed May 12, 2026, 6:11 p.m.
Created at: April 10, 2026, 10:25 a.m.