Triple

T5838709
Position Surface form Disambiguated ID Type / Status
Subject Pylons Project E129538 entity
Predicate supports P516 FINISHED
Object WSGI E129539 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: WSGI | Statement: [Pylons Project, supports, WSGI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WSGI
Context triple: [Pylons Project, supports, WSGI]
  • 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. Werkzeug WSGI utility library
    Werkzeug WSGI utility library is a comprehensive Python toolkit that provides utilities for building WSGI-compliant web applications and frameworks.
  • D. wsgiref
    wsgiref is a Python standard library package that provides reference implementations and utilities for working with WSGI-compatible web applications and servers.
  • 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_69c0084af79c81908af128ccc29983d0 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034a66c448190a6ea7f9827cbffe9 completed March 22, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0f371008190b11cd4da8a55dbb9 completed March 23, 2026, 3:18 a.m.
Created at: March 22, 2026, 3:54 p.m.