Visual and Systematic
Modern Terminology Management
With Coreon you build and access terminologies, taxonomies, ontologies, and vocabularies within one enterprise-scale multilingual knowledge graph.
Never lose control: Keep terminology clean and consistent for safe reuse in mission critical applications
One System, One View
360° Control through Systematic Approach
The Coreon Multilingual Knowledge System (MKS) unifies knowledge graphs with terminology: Terminological entries (concepts) are linked in the graph, while each entry itself is elaborated into potentially dozens of languages with unlimited descriptive and documentary information.
The knowledge graph is language neutral, the linking is not per term but per concept. This way the maintenance of the relations is not dependent from the labels, the terms and their variants, but happens efficiently only once per concept. Working on terms has no side-effects on the graph and vice versa. But they reside in one and the same resource.
Crafting terminology via a knowledge graph is the proven, very systematic methodology. It has immediate benefits and is a time-saver for the maintainers, the terminologists:
– Define concepts explicitly: relations make meanings explicit (‘engine’ IS-PART of ‘car’;
– Group concepts by semantic closeness: similar “things” are stored close to each other even when lexically very different (monitor – screen – display …);
– Navigate from generic to more specific: locate concepts you don’t know they are in (hardware -> input device -> microphone -> …);
– Keep up a high quality resource: see the gaps, identify the doublettes.
Through this systematic approach you keep control over a daily and ever growing resource, you share a trustful resource and ensure the data quality needed for Multilingual AI.
For Ad-HoC Users and ExPerts
Made for Organization-Wide Use
Global manufacturers rely on MKS to make their communication effective and efficient, in any language. This growing resource will not only be of value for authors or translators but is a knowledge treasure for all employees, suppliers, and customers.
However, a tool that lists thousands of terms only alphabetically is insufficient. It rather requires an underlying knowledge graph, a concept system: A concept, a unit of thought, is only well understood through its neighborhood, the more general, the more specific concepts and its siblings. Consider the concept ‘Tuesday’: it is explicitly defined and delimited through the existence of its siblings ‘Monday’ and ‘Wednesday’.
Users are no longer exhaustingly browsing through long word lists or glossaries. Instead they navigate smoothly through a rich visual map of connected concepts.
Deploy your MKS enterprise-wide: An innovative, very appealing user interface and ease-of-use is key for company-wide acceptance – no matter whether your are an ad-hoc user or an expert.
Leverage Existing Assets
Populate Your Multilingual Knowledge System
Microsoft Excel or Word lists, existing termbases in proprietary formats or in ISO TBX, W3C SKOS, RDF and other syntaxes … transform existing resources into an MKS. And even “flat” term lists can be fast transformed into a knowledge graph.
The visual concept map enables the semantic exploration of product information. Wordlist-like data collections that originated from authoring and translation are now usable for all knowledge workers and systems.
By elevating Terminology Management to multilingual knowledge it becomes part of a LangOps strategy and a critical resource of your companies’ information infrastructure.
Unlike tools that store terms in flat lists, Coreon links concepts in a language-neutral multilingual knowledge graph. This makes meanings explicit, duplicates easy to spot and terminology easy to navigate visually. Through REST and SPARQL APIs, it becomes a single source of truth for translation, content systems and AI.
Unlike ontology editors that treat words as simple labels, Coreon pairs a language-neutral knowledge graph with full multilingual terminology for each concept, i.e. not just one label per concept, but all synonyms with rich descriptive information such as part-of-speech, configurable usage status preferences etc. Images illustrate the meaning of concepts. It supports different kinds of relationships, multiple inheritance and SKOS/RDF/TBX. Its visual interface opens the graph to non-experts, and REST and SPARQL APIs connect it to other systems.
Coreon scales from small to enterprise-wide knowledge graphs. Customer repositories range from a few hundred to over 200,000 concepts, and Coreon has run graphs with more than 600,000 concepts and 7 million terms, such as the EU’s IATE termbase. Features like sections, breadcrumbs and multilingual search keep even very large graphs easy to navigate.
In as many as you need. Coreon links concepts, not words, so you maintain one language-neutral graph and every language is a view on it. Each concept can carry terms in dozens of languages, and users can browse the concept map or search in their preferred language. When you add a new language, the full structure is immediately available for it. There’s no separate taxonomy to build or synchronize per market.