Triple
T11215920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python generic class definitions |
E265439
|
entity |
| Predicate | introducedIn |
P513
|
FINISHED |
| Object | PEP 484 |
E265441
|
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: PEP 484 | Statement: [Python generic class definitions, introducedIn, PEP 484]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PEP 484 Context triple: [Python generic class definitions, introducedIn, PEP 484]
-
A.
PEP 484
chosen
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.
-
B.
PEP 585
PEP 585 is a Python Enhancement Proposal that introduced built-in generic types (like list[int] and dict[str, int]) as a modern replacement for many typing module aliases.
-
C.
PEP 604
PEP 604 is a Python Enhancement Proposal that introduced the modern, concise syntax for expressing type unions (using the `|` operator) in Python’s type hints.
-
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 624
PEP 624 is a Python Enhancement Proposal that specifies the removal of the Py_UNICODE encoder APIs from the CPython C API to streamline and modernize Unicode handling in Python.
- 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_69e4ad1c57908190a5c65ea4738722e3 |
completed | April 19, 2026, 10:23 a.m. |
Created at: April 8, 2026, 9:30 p.m.