Triple
T18051569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinja |
E431935
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Werkzeug |
—
|
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: Werkzeug | Statement: [Jinja, integratesWith, Werkzeug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werkzeug Context triple: [Jinja, integratesWith, Werkzeug]
-
A.
Werkzeug
chosen
Werkzeug is a widely used Python WSGI utility library that provides the low-level building blocks for web application frameworks such as Flask.
-
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.
Repyt
Repyt is an ancient Egyptian lioness goddess primarily worshipped at Akhmim, associated with protection and sometimes linked to solar and warlike aspects.
-
D.
Uvicorn
Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
-
E.
FLASK
FLASK is a flexible, fine-grained security architecture originally developed for operating systems like SELinux to support configurable mandatory access control policies.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c0fe4f1881908fa8485cb3ccfa44 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:25 a.m.