Triple
T11215860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type Parameter Syntax |
E265437
|
entity |
| Predicate | category |
P87
|
FINISHED |
| Object | Python generics |
E265438
|
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 generics | Statement: [Type Parameter Syntax, category, Python generics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Python generics Context triple: [Type Parameter Syntax, category, Python generics]
-
A.
Python generic types
chosen
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.
-
B.
Python generic class definitions
Python generic class definitions are type-parameterized class constructs that enable writing reusable, type-safe classes using Python’s static type system.
-
C.
Python generic function definitions
Python generic function definitions are a proposed language feature that allows functions to be parameterized by type variables, enabling more precise static typing and reusable, type-safe code.
-
D.
.NET generics
.NET generics are a type system feature in the .NET framework that enables type-safe, reusable, and efficient data structures and methods by allowing code to be written with placeholder types.
-
E.
Python typing module
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.
- 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.