Triple

T1041725
Position Surface form Disambiguated ID Type / Status
Subject PHP E22482 entity
Predicate influenced P9 FINISHED
Object Twig (templating language) E96622 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: Twig (templating language) | Statement: [PHP, influenced, Twig (templating language)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Twig (templating language)
Context triple: [PHP, influenced, Twig (templating language)]
  • 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. SpaceShipTwo
    SpaceShipTwo is a suborbital spaceplane developed for Virgin Galactic’s commercial space tourism program, designed to carry passengers to the edge of space for brief periods of weightlessness.
  • C. Elm
    Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
  • D. Elm
    Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
  • E. Svelte
    Svelte is a modern JavaScript framework and compiler for building user interfaces that shifts much of the work to a build step, producing highly efficient, minimal runtime code.
  • 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b82f6c14819080277443ea4722dd completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bc768948190b1cda4eea93fe4b6 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:42 p.m.