Triple

T18015753
Position Surface form Disambiguated ID Type / Status
Subject Bottle E430994 entity
Predicate supports P516 FINISHED
Object Jinja2 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: Jinja2 | Statement: [Bottle, supports, Jinja2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jinja2
Context triple: [Bottle, supports, Jinja2]
  • A. Jinja2 chosen
    Jinja2 is a popular Python templating engine used to generate dynamic HTML and other text-based formats, known for its Django-inspired syntax and integration with web frameworks like Flask.
  • B. Jinja
    Jinja is a popular and powerful templating engine for Python, widely used for generating dynamic HTML in web applications and frameworks like Flask.
  • C. Jinja
    Jinja is a major town in southeastern Uganda, known as a key industrial center and a popular tourist destination near the source of the Nile River.
  • D. Nunjucks
    Nunjucks is a powerful JavaScript templating engine, inspired by Jinja2, commonly used to generate dynamic HTML in web applications and design systems.
  • E. Twig
    Twig is a modern, secure, and flexible templating engine for PHP, widely used to separate presentation from application logic in frameworks like Symfony.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b523f588819097389e067dda7f23 completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.