Triple

T8816635
Position Surface form Disambiguated ID Type / Status
Subject Apache HTTP Server E209792 entity
Predicate supportsExtensionModule P38742 FINISHED
Object mod_wsgi E96631 NE FINISHED

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: [Apache HTTP Server, supportsExtensionModule, mod_wsgi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: mod_wsgi
Context triple: [Apache HTTP Server, supportsExtensionModule, 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. wsgiref
    wsgiref is a Python standard library package that provides reference implementations and utilities for working with WSGI-compatible web applications and servers.
  • D. mod_proxy
    mod_proxy is an Apache HTTP Server module that provides proxy and gateway functionality, enabling features like load balancing, reverse proxying, and protocol tunneling for web applications.
  • E. uWSGI
    uWSGI is a high-performance application server commonly used to run Python web applications in production, often sitting between web frameworks and web servers like Nginx.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8364e13081909c85fe80f44fe86f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc600bd8a88190ad891a96201d796b completed April 1, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_69cf6fc1579c8190ade0f780183aa1dc completed April 3, 2026, 7:44 a.m.
Created at: March 30, 2026, 6:46 p.m.