Triple

T4325446
Position Surface form Disambiguated ID Type / Status
Subject Flask-WTF E96624 entity
Predicate integratesWith P1075 FINISHED
Object WTForms
WTForms is a flexible Python library for creating and validating web forms, commonly used in web frameworks like Flask.
 E430981 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: WTForms | Statement: [Flask-WTF, integratesWith, WTForms]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WTForms
Context triple: [Flask-WTF, integratesWith, WTForms]
  • A. Flask-WTF
    Flask-WTF is a Flask extension that integrates WTForms to simplify web form creation, validation, and CSRF protection in Flask applications.
  • B. Flask-Admin
    Flask-Admin is a popular Flask extension that provides a flexible, customizable administrative interface for managing application data and models.
  • C. Flask
    Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
  • D. Flask
    Flask is a minor but tough and pugnacious third mate aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
  • E. 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.
  • 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: WTForms
Triple: [Flask-WTF, integratesWith, WTForms]
Generated description
WTForms is a flexible Python library for creating and validating web forms, commonly used in web frameworks like Flask.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WTForms
Target entity description: WTForms is a flexible Python library for creating and validating web forms, commonly used in web frameworks like Flask.
  • A. Flask-WTF
    Flask-WTF is a Flask extension that integrates WTForms to simplify web form creation, validation, and CSRF protection in Flask applications.
  • B. Flask-Admin
    Flask-Admin is a popular Flask extension that provides a flexible, customizable administrative interface for managing application data and models.
  • C. Flask
    Flask is a lightweight, flexible Python micro web framework designed for building web applications and APIs with minimal boilerplate.
  • D. Flask
    Flask is a minor but tough and pugnacious third mate aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
  • E. 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.
  • 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_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_69b5d09861a4819086a88bb42a8ea2e4 completed March 14, 2026, 9:18 p.m.
NEDg Description generation batch_69b5d11a30a08190b9f58fadd2415559 completed March 14, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_69b5d194975481908b029ab106223c6c completed March 14, 2026, 9:22 p.m.
Created at: March 12, 2026, 11:13 p.m.