Triple
T14327719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | vi |
E355255
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Vim |
E308599
|
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: Vim | Statement: [vi, influenced, Vim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vim Context triple: [vi, influenced, 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 (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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c1c3e70819084b6728ac5c18561 |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46927af48190b91095d852fcacbe |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:13 a.m.