Triple

T17519658
Position Surface form Disambiguated ID Type / Status
Subject Swagger Codegen E426651 entity
Predicate supportsLanguage P2177 FINISHED
Object Elixir 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: Elixir | Statement: [Swagger Codegen, supportsLanguage, Elixir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elixir
Context triple: [Swagger Codegen, supportsLanguage, Elixir]
  • A. Elixir chosen
    Elixir is a functional, concurrent programming language built on the Erlang VM, known for its scalability, fault tolerance, and expressive syntax.
  • B. Erlang
    Erlang is a functional, concurrent programming language designed for building highly scalable, fault-tolerant distributed systems, originally developed by Ericsson for telecom applications.
  • C. Phoenix Framework
    Phoenix Framework is an Elixir-based web development framework known for its high performance, real-time capabilities, and productive developer experience inspired by Ruby on Rails.
  • D. Elm
    Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
  • E. Elm
    Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d18c1c81908bb843bbddb44ca1 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.