Triple

T11215971
Position Surface form Disambiguated ID Type / Status
Subject Python generic function definitions E265440 entity
Predicate relatedTo P37 FINISHED
Object Python typing module E887713 NE FINISHED

How this triple was built (2 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: Python typing module | Statement: [Python generic function definitions, relatedTo, Python typing module]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python typing module
Context triple: [Python generic function definitions, relatedTo, Python typing module]
  • A. Python typing module chosen
    The Python typing module is a standard library component that adds support for type hints and static type checking to Python code, enabling clearer interfaces and improved tooling.
  • B. PEP 484
    PEP 484 is the Python Enhancement Proposal that introduced a standard for type hints in Python, forming the basis of the language’s static typing ecosystem.
  • C. typer
    Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), the author of FastAPI.
  • D. Python generic types
    Python generic types are a type system feature that allows developers to write functions, classes, and data structures that operate on values of multiple types while preserving static type information.
  • E. PEP 647 TypeGuard
    PEP 647 TypeGuard is a Python typing feature that allows developers to define user-defined type guard functions, enabling more precise type narrowing and improved static type checking.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8e8eef48190932a85784ce15c86 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e49762e3188190ba3c0e01cf04f6a1 completed April 19, 2026, 8:50 a.m.
Created at: April 8, 2026, 9:30 p.m.