Triple

T4442655
Position Surface form Disambiguated ID Type / Status
Subject Ruby on Rails E96207 entity
Predicate influenced P9 FINISHED
Object Laravel E120464 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: Laravel | Statement: [Ruby on Rails, influenced, Laravel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laravel
Context triple: [Ruby on Rails, influenced, Laravel]
  • A. Laravel chosen
    Laravel is a popular open-source PHP web application framework known for its elegant syntax, robust tooling, and support for rapid application development.
  • B. Slim Framework
    Slim Framework is a lightweight PHP micro-framework designed for building simple yet powerful web applications and APIs with minimal overhead.
  • C. CakePHP
    CakePHP is an open-source rapid development web framework for PHP that follows the MVC pattern and emphasizes convention over configuration to streamline building web applications.
  • D. Quasar Framework
    Quasar Framework is a high-performance, Vue.js-based UI framework for building responsive web, mobile, and desktop applications from a single codebase.
  • E. Ruby on Rails
    Ruby on Rails is a popular open-source web application framework that emphasizes convention over configuration and rapid development for building database-backed applications.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355aef21c819088f168a23f1933a6 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61382d00481908b7c84f337b5cad7 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:32 p.m.