Triple

T4683312
Position Surface form Disambiguated ID Type / Status
Subject Dash E103855 entity
Predicate basedOn P98 FINISHED
Object Flask E17841 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: Flask | Statement: [Dash, basedOn, Flask]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flask
Context triple: [Dash, basedOn, 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. Django
    Django is a 1966 Italian Spaghetti Western film directed by Sergio Corbucci and starring Franco Nero as a mysterious gunslinger, renowned for its gritty style and influential impact on the genre.
  • D. Django
    Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design for building secure, scalable web applications.
  • 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 (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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd638130a08190876c5829c0488758 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03b07664819097d959fde1b0585b completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:16 p.m.