Triple

T18051515
Position Surface form Disambiguated ID Type / Status
Subject Armin Ronacher E431934 entity
Predicate notableWork P4 FINISHED
Object Flask web framework 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 web framework | Statement: [Armin Ronacher, notableWork, Flask web framework]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flask web framework
Context triple: [Armin Ronacher, notableWork, Flask web framework]
  • 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. Starlette web framework
    Starlette is a lightweight, high-performance ASGI web framework for Python, designed for building asynchronous web services and APIs.
  • E. Flask-RESTful
    Flask-RESTful is a popular Flask extension that simplifies building RESTful APIs by providing tools for request parsing, input validation, and structured resource routing.
  • 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.