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Jakub je mužské křestní jméno. Podle českého kalendáře má svátek 25. července.
The analysis highlights Známí nositelé jména, Jakub v jiných jazycích and Statistické údaje as prominent areas in the source structure around Jakub.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
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Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
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The extracted context around Jakub shows recurring relationship patterns in the source. For example, Jakub → Bažant, Bouda, Deml, Elordi, Flek, František Stuart, Grigar, Holuša, II, Jacques Rousseau, Jakob Anund, Jan Ryba, Janda, Jurovskij, Klepiš, Kohák, Krčín, Lauko, Maradona, Menšík Another extracted example is Jakub → Diego, Giacobbe, GiacomoŠpanělsky, Jaakko, Jacob, JacobFrancouzsky, Jacobo, JacquelineItalsky, Jacques, Jago, Jaime, JakabHebrejsky, JakobAnglicky, Jakov, JakubNěmecky, Jakup, JamesAlbánsky, Maďarsky, Nizozemsky, SantiagoRusky. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
jméno sv jména diego nejčastější mužské 25 jakuba jacob četnost jakob král biblický patriarcha původ česko červenec údaje čr 1999
TTTA extracted 105 structured relationships around Jakub. Examples in this analysis include Jakub → Diego → 129 (944. nejčastější) and Jakub → Domácí podoby → Jakoubek, Jakeš, Jašek, Kubík, Kuba. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Jakub | Diego | 129 (944. nejčastější) | 1.00 | infobox |
| Jakub | Domácí podoby | Jakoubek, Jakeš, Jašek, Kubík, Kuba | 1.00 | infobox |
| Jakub | Jacob | 115 (995. nejčastější) | 1.00 | infobox |
| Jakub | Jakob | 79 (1 167. nejčastější) | 1.00 | infobox |
| Jakub | Pořadí podle četnosti | 22. | 1.00 | infobox |
| Jakub | Původ | hebrejský | 1.00 | infobox |
| Jakub | Česko Česko | 25. červenec | 1.00 | infobox |
| Jakub | Četnost v Česku | 108 013 | 1.00 | infobox |
| Jakub | Ženská podoba | Jakuba, Jakubka, Žakelina, Žakelína | 1.00 | infobox |
| Jakub | related to Jakub v jiných jazycích | Slovensky | 0.60 | section |
| Jakub | related to Jakub v jiných jazycích | JakubNěmecky | 0.60 | section |
| Jakub | related to Jakub v jiných jazycích | JakobAnglicky | 0.60 | section |
The concept neighborhoods around Jakub bring nearby vocabulary together. In this analysis, examples include Jméno, Jakuba and Sv. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Jakub, one of the stronger structural bridges in this analysis connects Jakub with Známí nositelé jména. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Jakub to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Známí nositelé jména, Jakub v jiných jazycích & Statistické údaje, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Jakub · CS edition · Analysis: TopicsToTalkAbout
