Triple

T18015762
Position Surface form Disambiguated ID Type / Status
Subject Bottle E430994 entity
Predicate supports P516 FINISHED
Object wsgiref 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: wsgiref | Statement: [Bottle, supports, wsgiref]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: wsgiref
Context triple: [Bottle, supports, wsgiref]
  • A. wsgiref chosen
    wsgiref is a Python standard library package that provides reference implementations and utilities for working with WSGI-compatible web applications and servers.
  • B. Werkzeug WSGI utility library
    Werkzeug WSGI utility library is a comprehensive Python toolkit that provides utilities for building WSGI-compliant web applications and frameworks.
  • C. WSGI
    WSGI (Web Server Gateway Interface) is a Python standard that defines a common interface between web servers and Python web applications or frameworks.
  • D. Waitress WSGI server
    Waitress WSGI server is a production-quality, pure-Python WSGI server designed for serving Python web applications simply and reliably.
  • E. WebOb
    WebOb is a Python library that provides a WSGI-based abstraction layer for HTTP request and response handling in web applications.
  • 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.