Triple

T18529871
Position Surface form Disambiguated ID Type / Status
Subject Fabien Potencier E452805 entity
Predicate notableWork P4 FINISHED
Object Twig template engine 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: Twig template engine | Statement: [Fabien Potencier, notableWork, Twig template engine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Twig template engine
Context triple: [Fabien Potencier, notableWork, Twig template engine]
  • A. Twig chosen
    Twig is a modern, secure, and flexible templating engine for PHP, widely used to separate presentation from application logic in frameworks like Symfony.
  • B. Jinja2
    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.
  • C. Twirl template engine
    Twirl template engine is a Scala-based HTML templating system used to generate dynamic web pages, notably integrated into the Play Framework.
  • D. SimpleTemplate
    SimpleTemplate is Bottle’s built-in lightweight templating engine designed for embedding Python code directly into HTML.
  • E. Slim Twig-View
    Slim Twig-View is an extension for the Slim PHP framework that integrates the Twig templating engine to render views in Slim applications.
  • 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e533fb940c81909d4ad9fc37f47829 completed April 19, 2026, 7:58 p.m.
Created at: April 10, 2026, 11:37 a.m.