Triple

T17517367
Position Surface form Disambiguated ID Type / Status
Subject PlatformIO E426601 entity
Predicate supportsEditor P15794 FINISHED
Object Vim 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: Vim | Statement: [PlatformIO, supportsEditor, Vim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vim
Context triple: [PlatformIO, supportsEditor, Vim]
  • A. Vim chosen
    Vim is a highly configurable, keyboard-driven text editor renowned for its efficiency, modal editing, and extensive plugin ecosystem, widely used by programmers and power users.
  • B. VIM
    VIM is a company that employs Diane Nguyen, likely operating in a professional or corporate services field.
  • C. Neovim
    Neovim is a modern, extensible, and highly configurable fork of the Vim text editor, designed to improve usability, maintainability, and plugin integration for developers.
  • D. MacVim
    MacVim is a macOS-native graphical version of the Vim text editor that integrates with the Mac user interface while preserving Vim’s modal editing features.
  • E. Sublime Text
    Sublime Text is a fast, cross-platform, extensible text editor popular among developers for its powerful features and plugin ecosystem.
  • 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452615a8481909974e9855ea7a8e4 completed April 19, 2026, 3:56 a.m.
Created at: April 10, 2026, 5:49 a.m.