Triple
T22330648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP 333 |
E552012
|
entity |
| Predicate | definesTerm |
P773
|
FINISHED |
| Object | WSGI application |
—
|
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: WSGI application | Statement: [PEP 333, definesTerm, WSGI application]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WSGI application Context triple: [PEP 333, definesTerm, WSGI application]
-
A.
WSGI
chosen
WSGI (Web Server Gateway Interface) is a Python standard that defines a common interface between web servers and Python web applications or frameworks.
-
B.
ASGI
ASGI (Asynchronous Server Gateway Interface) is a Python standard for asynchronous web servers and applications that enables high-performance, concurrent web frameworks and services.
-
C.
Waitress WSGI server
Waitress WSGI server is a production-quality, pure-Python WSGI server designed for serving Python web applications simply and reliably.
-
D.
Werkzeug WSGI utility library
Werkzeug WSGI utility library is a comprehensive Python toolkit that provides utilities for building WSGI-compliant web applications and frameworks.
-
E.
wsgiref
wsgiref is a Python standard library package that provides reference implementations and utilities for working with WSGI-compatible web applications and servers.
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577a9c348190b8662142afa832be |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:43 p.m.