Triple
T18051355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | wsgiref |
E431932
|
entity |
| Predicate | implements |
P1417
|
FINISHED |
| Object | PEP 333 |
—
|
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: PEP 333 | Statement: [wsgiref, implements, PEP 333]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PEP 333 Context triple: [wsgiref, implements, PEP 333]
-
A.
PEP 333
chosen
PEP 333 is the Python Enhancement Proposal that originally defined the Web Server Gateway Interface (WSGI), a standard for communication between Python web applications and web servers.
-
B.
PEP 343
PEP 343 is the Python Enhancement Proposal that introduced the "with" statement and the context manager protocol to simplify resource management in Python.
-
C.
PEP 328
PEP 328 is a Python Enhancement Proposal that introduced and standardized the syntax and semantics for absolute and relative imports in Python.
-
D.
PEP 302
PEP 302 is a Python Enhancement Proposal that defines the import hook mechanism, enabling customization and extension of Python’s module import system.
-
E.
PEP 345
PEP 345 is a Python Enhancement Proposal that defines the metadata format for Python software packages, including standardized fields used in package distribution.
- 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_69e4c0fe4f1881908fa8485cb3ccfa44 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:25 a.m.