Triple
T5838850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zope |
E129541
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
Grok (web framework)
Grok is a Python-based web framework that emphasizes convention over configuration and rapid development, built on top of the Zope toolkit.
|
E551827
|
NE FINISHED |
How this triple was built (4 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 (web framework) | Statement: [Zope, influenced, Grok (web framework)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grok (web framework) Context triple: [Zope, influenced, Grok (web framework)]
-
A.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
-
B.
Werkzeug
Werkzeug is a widely used Python WSGI utility library that provides the low-level building blocks for web application frameworks such as Flask.
-
C.
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.
-
D.
Grok! Television
Grok! Television is a production company known for its involvement in creating the first season of the acclaimed fantasy television series "Game of Thrones."
-
E.
Uvicorn
Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Grok (web framework) Triple: [Zope, influenced, Grok (web framework)]
Generated description
Grok is a Python-based web framework that emphasizes convention over configuration and rapid development, built on top of the Zope toolkit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grok (web framework) Target entity description: Grok is a Python-based web framework that emphasizes convention over configuration and rapid development, built on top of the Zope toolkit.
-
A.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
-
B.
Werkzeug
Werkzeug is a widely used Python WSGI utility library that provides the low-level building blocks for web application frameworks such as Flask.
-
C.
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.
-
D.
Grok! Television
Grok! Television is a production company known for its involvement in creating the first season of the acclaimed fantasy television series "Game of Thrones."
-
E.
Uvicorn
Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69c0a572f52481908fc4f2a833fd8edf |
completed | March 23, 2026, 2:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0a5d17d5c8190a5fe816d29400894 |
completed | March 23, 2026, 2:30 a.m. |
Created at: March 22, 2026, 3:54 p.m.