Triple
T22387056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zope Component Architecture |
E553421
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | Grok framework |
—
|
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: Grok framework | Statement: [Zope Component Architecture, usedIn, Grok framework]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grok framework Context triple: [Zope Component Architecture, usedIn, Grok framework]
-
A.
Grok (web framework)
chosen
Grok is a Python-based web framework that emphasizes convention over configuration and rapid development, built on top of the Zope toolkit.
-
B.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
-
C.
Koa web framework
Koa is a minimalist, modern Node.js web framework designed by TJ Holowaychuk to provide a smaller, more expressive, and robust foundation for web applications and APIs using async functions.
-
D.
GRO
GRO is the FAA airport code assigned to Rota International Airport, a public airport serving the island of Rota in the Northern Mariana Islands.
-
E.
GRO
GRO is the station code used to identify Grove Street station on the Newark Light Rail system in New Jersey.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158304bcc81908c4c5db09a246bcc |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.