Triple

T4325468
Position Surface form Disambiguated ID Type / Status
Subject Flask-WTF E96624 entity
Predicate requires P100 FINISHED
Object WTForms E430981 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: WTForms | Statement: [Flask-WTF, requires, WTForms]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WTForms
Context triple: [Flask-WTF, requires, WTForms]
  • A. WTForms chosen
    WTForms is a flexible Python library for creating and validating web forms, commonly used in web frameworks like Flask.
  • B. Flask-WTF
    Flask-WTF is a Flask extension that integrates WTForms to simplify web form creation, validation, and CSRF protection in Flask applications.
  • C. Flask-Admin
    Flask-Admin is a popular Flask extension that provides a flexible, customizable administrative interface for managing application data and models.
  • D. Flask-Security
    Flask-Security is a Flask extension that provides a unified, high-level interface for handling authentication, authorization, user registration, and role management in web applications.
  • E. Flask
    Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
  • 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_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3512ec18481908a7b5c29b3902b53 completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db98ae888190aac5b5b7839ae7dd completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:13 p.m.