Triple

T2889631
Position Surface form Disambiguated ID Type / Status
Subject Spacemacs E59586 entity
Predicate supportsProgrammingLanguage P1592 FINISHED
Object Elixir E96206 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: Elixir | Statement: [Spacemacs, supportsProgrammingLanguage, Elixir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elixir
Context triple: [Spacemacs, supportsProgrammingLanguage, 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. 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. Rubinius
    Rubinius is an alternative Ruby implementation featuring a virtual machine and just-in-time compilation, designed for high performance and concurrency.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe04a68ac8190aaeafe52138beb74 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03179d7448190bcdbea164856aaa2 completed March 10, 2026, 2:58 p.m.
Created at: March 6, 2026, 10:04 p.m.