Triple
T825412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flask |
E17841
|
entity |
| Predicate | extensionEcosystem |
P11253
|
FINISHED |
| Object |
Flask-Caching
Flask-Caching is a Flask extension that provides easy-to-use caching support to improve the performance and scalability of Flask web applications.
|
E96628
|
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: Flask-Caching | Statement: [Flask, extensionEcosystem, Flask-Caching]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flask-Caching Context triple: [Flask, extensionEcosystem, Flask-Caching]
-
A.
Flask
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.
Django
Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design for building secure, scalable web applications.
-
D.
FastAPI
FastAPI is a modern, high-performance Python framework for building APIs with automatic interactive documentation and type hint–driven validation.
-
E.
Stackless Python
Stackless Python is an enhanced version of the Python interpreter that provides lightweight microthreads and improved concurrency support without relying on the C call stack.
- 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: Flask-Caching Triple: [Flask, extensionEcosystem, Flask-Caching]
Generated description
Flask-Caching is a Flask extension that provides easy-to-use caching support to improve the performance and scalability of Flask web applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Flask-Caching Target entity description: Flask-Caching is a Flask extension that provides easy-to-use caching support to improve the performance and scalability of Flask web applications.
-
A.
Flask
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.
Django
Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design for building secure, scalable web applications.
-
D.
FastAPI
FastAPI is a modern, high-performance Python framework for building APIs with automatic interactive documentation and type hint–driven validation.
-
E.
Stackless Python
Stackless Python is an enhanced version of the Python interpreter that provides lightweight microthreads and improved concurrency support without relying on the C call stack.
- 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_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_69a76d9577f081908aa31b1926e04bb8 |
completed | March 3, 2026, 11:24 p.m. |
| NEDg | Description generation | batch_69a78204c1208190b2d2d19cdea93b57 |
completed | March 4, 2026, 12:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a78648601881908bfcb9390ac4d6d2 |
completed | March 4, 2026, 1:09 a.m. |
Created at: March 1, 2026, 7:38 p.m.