A comprehensive development environment for SUMO (SUO-KIF) and TPTP in Visual Studio Code. This extension provides advanced language intelligence, Knowledge Base (KB) management, interactive taxonomy browsing, and seamless theorem prover integration.
Manage your Sigma Knowledge Bases directly from the sidebar.
- Open KB: Automatically detect and load KBs from your Sigma
config.xml. - Add/Remove Files: Easily manage constituent
.kiffiles. - Create KB: Scaffold new knowledge bases with a simple guided process.
- Context Awareness: The extension tracks which KB you are currently working in, enabling KB-specific search and navigation.
Rich support for the SUO-KIF and TPTP languages used by SUMO:
- Go to Definition (F12): Jump to where a term is defined via
instance,subclass,domain, etc. - Hover & Autocomplete: View documentation and argument types (from
domaindeclarations) as you type. - Signature Help: Real-time guidance on relation arguments while writing axioms.
- Diagnostics: Instant feedback on syntax errors, naming conventions, and arity mismatches.
Visualize the ontology structure with a dedicated webview:
- Ancestor & Descendant Trees: Explore the hierarchy of any class or relation.
- Inline Documentation: Read the
documentationstrings for terms as you browse. - Interactive Navigation: Right-click nodes to focus on a new term or search for its occurrences in the workspace.
Flexibility in how you run Sigma translation logic:
- Local: Uses your local SigmaKEE installation (requires Java).
- Docker: Connects to a running SigmaKEE docker container. NOTE: This does not work currently
- Native JS (Experimental): A built-in JavaScript implementation for TPTP conversion—no external dependencies required. *NOTE: This is purely experimental! Use at your own risk and check all results against actual output from Sigma
Verify your axioms with theorem provers like Vampire and E-Prover:
- Query Prover: Select an axiom and run it as a conjecture against your workspace.
- Scope-based Verification: Run the prover on a selection, the current file, or the entire workspace.
- TPTP Generation: Export your SUMO KBs to TPTP (
fof,tff, orthfformats).
| Command | Keybinding | Context |
|---|---|---|
SUMO: Open Knowledge Base |
Command Palette | |
SUMO: Search Symbol in Workspace |
Editor Context / Palette | |
SUMO: Go to Definition |
F12 |
Editor Context |
SUMO: Format Axiom |
Ctrl+Shift+F |
Editor Context (Selection) |
SUMO: Show Class Taxonomy |
Editor Context / Palette | |
SUMO: Browse Term in Sigma |
Ctrl+Shift+B |
Editor Context |
SUMO: Query with Theorem Prover |
Editor Context (Selection) | |
SUMO: Check for Errors |
Editor Context / Palette | |
SUMO: Generate TPTP File |
Command Palette |
Access these settings via File > Preferences > Settings (search for "SUMO"):
sumo.general.language: Language for documentation (default:EnglishLanguage).sumo.general.formatIndentSize: Number of spaces for indentation (default:2).
sumo.sigma.runtime: Choose betweenlocal,docker, ornative.sumo.sigma.configXmlPath: Explicit path to Sigma'sconfig.xml.sumo.sigma.url: The URL for the online Sigma browser.
sumo.theoremProver.path: Path to your prover executable (Vampire/E).sumo.theoremProver.type: Prover type (vampireoreprover).sumo.theoremProver.timeout: Seconds before the prover gives up (default:30).sumo.theoremProver.tptpLang: TPTP format (fof,tff, orthf).
- VSCode 1.70.0+
- (Optional) Java for Local Sigma runtime.
- (Optional) Docker for Docker Sigma runtime.
- (Optional) Vampire or E-Prover for theorem proving features.
License: MIT Credits: Developed by the Ontology Portal community.
Niles, I., and Pease, A. 2001. Towards a Standard Upper Ontology. In
Proceedings of the 2nd International Conference on Formal Ontology in
Information Systems (FOIS-2001), Chris Welty and Barry Smith, eds,
Ogunquit, Maine, October 17-19, 2001. Also see http://www.ontologyportal.org
G. Sutcliffe, “Stepping Stones in the TPTP World,” in Proc. 12th Int. Joint Conf. Automated Reasoning, vol. 14739, C. Benzmüller, M. Heule, and R. Schmidt, Eds. Nancy, France: Lecture Notes in Artificial Intelligence, 2024, pp. 30–50.



