Triple
T5838855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zope |
E129541
|
entity |
| Predicate | hasVersion |
P455
|
FINISHED |
| Object | Zope 4 |
E129541
|
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: Zope 4 | Statement: [Zope, hasVersion, Zope 4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zope 4 Context triple: [Zope, hasVersion, Zope 4]
-
A.
Zope
chosen
Zope is an open-source web application server and framework for the Python programming language, known for pioneering object publishing and component-based web development.
-
B.
Zope Component Architecture integration
Zope Component Architecture integration is a system that brings Zope’s flexible component and adapter patterns into other Python frameworks to enable modular, pluggable application design.
-
C.
Werkzeug
Werkzeug is a widely used Python WSGI utility library that provides the low-level building blocks for web application frameworks such as Flask.
-
D.
Zeta platform
Zeta platform is a General Motors-developed digital vehicle software and connectivity platform designed to power in-car services, data, and user experiences.
-
E.
repoze.bfg
repoze.bfg is the former name of Pyramid, a lightweight Python web framework focused on flexibility and scalability.
- 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_69c034a852f88190a5d2c4b24ee17491 |
completed | March 22, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a19e4ec4819099fa5c6fe9a6a257 |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:54 p.m.