Triple
T18015673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WSGIRestrictStdout |
E430992
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | mod_wsgi |
—
|
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: mod_wsgi | Statement: [WSGIRestrictStdout, partOf, mod_wsgi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: mod_wsgi Context triple: [WSGIRestrictStdout, partOf, mod_wsgi]
-
A.
mod_wsgi
chosen
mod_wsgi is an Apache HTTP Server module that hosts Python-based web applications using the WSGI interface, commonly used to deploy frameworks like Flask and Django in production.
-
B.
WSGI
WSGI (Web Server Gateway Interface) is a Python standard that defines a common interface between web servers and Python web applications or frameworks.
-
C.
mod_ssl
mod_ssl is an Apache HTTP Server module that provides SSL/TLS encryption and HTTPS support for secure web communication.
-
D.
mod_perl
mod_perl is an Apache HTTP Server module that embeds a Perl interpreter to dramatically speed up Perl CGI scripts and enable powerful server-side Perl integration.
-
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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.