Triple
T18051018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | typing (Python module) |
E431925
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | mypy |
—
|
NE NERFINISHED |
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: mypy | Statement: [typing (Python module), usedBy, mypy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: mypy Context triple: [typing (Python module), usedBy, mypy]
-
A.
mypy
chosen
mypy is a static type checker for Python that enforces type hints and helps catch type-related errors before runtime.
-
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.
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.
-
D.
typer
Typer is a modern, user-friendly Python library for building command-line interfaces, created by Sebastián Ramírez (tiangolo), the author of FastAPI.
-
E.
Pydantic
Pydantic is a Python library for data validation and settings management that uses type hints to parse, validate, and serialize data.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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. |
Created at: April 10, 2026, 10:25 a.m.