Triple
T22387034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waitress |
E553420
|
entity |
| Predicate | usedWithFramework |
P4791
|
FINISHED |
| Object | Flask |
—
|
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: Flask | Statement: [Waitress, usedWithFramework, Flask]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flask Context triple: [Waitress, usedWithFramework, Flask]
-
A.
Flask
chosen
Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
-
B.
Flask
Flask is a minor but tough and pugnacious third mate aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
-
C.
FLASK
FLASK is a flexible, fine-grained security architecture originally developed for operating systems like SELinux to support configurable mandatory access control policies.
-
D.
Pylons web framework
Pylons is a lightweight, Python-based web framework focused on flexibility and reusability, combining components from multiple libraries to build web applications.
-
E.
Django
"Django" is a celebrated jazz composition by pianist John Lewis, best known through performances by the Modern Jazz Quartet and regarded as one of their signature pieces.
- 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.