Triple
T18051375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | wsgiref.simple_server |
E431932
|
entity |
| Predicate | provides |
P490
|
FINISHED |
| Object | WSGIServer class |
—
|
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: WSGIServer class | Statement: [wsgiref.simple_server, provides, WSGIServer class]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WSGIServer class Context triple: [wsgiref.simple_server, provides, WSGIServer class]
-
A.
WSGI
WSGI (Web Server Gateway Interface) is a Python standard that defines a common interface between web servers and Python web applications or frameworks.
-
B.
Waitress WSGI server
Waitress WSGI server is a production-quality, pure-Python WSGI server designed for serving Python web applications simply and reliably.
-
C.
wsgiref
chosen
wsgiref is a Python standard library package that provides reference implementations and utilities for working with WSGI-compatible web applications and servers.
-
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.
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.
- 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.