Triple
T825416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flask |
E17841
|
entity |
| Predicate | deploymentTargets |
P12960
|
FINISHED |
| Object | Gunicorn |
E97063
|
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: Gunicorn | Statement: [Flask, deploymentTargets, Gunicorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gunicorn Context triple: [Flask, deploymentTargets, Gunicorn]
-
A.
Uvicorn
Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
-
B.
Gunicorn (with ASGI workers)
chosen
Gunicorn (with ASGI workers) is a Python WSGI/ASGI HTTP server that can run asynchronous web frameworks like FastAPI in a robust, production-ready environment.
-
C.
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.
-
D.
Flask
Flask is a minor but tough and pugnacious third mate aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
-
E.
Flask
Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b503d48190bd4f33548a22d5fe |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a79291d51c81908163024842300a6e |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.