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XBoard is a graphical user interface chessboard for chess engines under the X Window System. It is developed and maintained as free software by the GNU project. WinBoard is a port of XBoard to run natively on Microsoft Windows.
Fairy-Max & Overview
Explore the main themes, entities and connections around XBoard. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| XBoard | Developer | GNU project | 1.00 | infobox |
| XBoard | License | GPL | 1.00 | infobox |
| XBoard | Operating system | Linux, FreeBSD, NetBSD, OpenBSD, Microsoft Windows, macOS | 1.00 | infobox |
| XBoard | Repository | git.savannah.gnu.org/cgit/xboard.git | 1.00 | infobox |
| XBoard | Stable release | 4.9.1 / 1 August 2016 | 1.00 | infobox |
| XBoard | Type | Computer chess | 1.00 | infobox |
| XBoard | Website | XBoard | 1.00 | infobox |
| XBoard | is a | graphical user interface chessboard for chess engines under the X Window System | 0.90 | text |
| hash tables | instance of | which have features | 0.80 | text |
| multi-processing | instance of | which have features | 0.80 | text |
| end-game tables | instance of | which have features | 0.80 | text |
| which could not be controlled through the old protocol | instance of | which have features | 0.80 | text |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.