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Vlastní mužské jméno Petr pochází z řečtiny (πέτρος Petros), kde femininum πέτρα petra znamená „kámen“ či „skála“ . V České republice to bylo v roce 2016 třetí nejčetnější jméno.
The analysis highlights Petr v jiných jazycích, Významné osoby and Data jmenin as prominent areas in the source structure around Petr.
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.
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.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Petr shows recurring relationship patterns in the source. For example, Petr → Bedeuro, Bedros, Boutros, Butrus, Bóduōlù, Bǐdé, Kepa, Pathrose, Pathrus, Patraspolsky, Peadarislandsky, Peder, Pederkorsicky, Pedr, Pedrosrbsky, Pedrukorejsky, Peer, Peerchorvatsky, Peeterfaersky, Peio Another extracted example is Petr → Alexandrijský, Canisius, Celestýn, Chanel, Chrysolog, Faber, Ferdinand Toskánský, II, III, KolumbiiPetr Damián, Nikolajevič Ruský, Petr Claver, Petra, Ruský, Velikého, Veliký. 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 jména petra ruský 29 června čr února petros mužské příjmení peter kalendáři více osob car 1762 tohoto 22 četnost
TTTA extracted 125 structured relationships around Petr. Examples in this analysis include Petr → Podle údajů z roku → 2013 and Petr → Pořadí podle četnosti → 2.. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Petr | Podle údajů z roku | 2013 | 1.00 | infobox |
| Petr | Pořadí podle četnosti | 2. | 1.00 | infobox |
| Petr | Původ | řecký | 1.00 | infobox |
| Petr | Svátky | 22. února 29. června | 1.00 | infobox |
| Petr | Četnost v Česku | 272 135 | 1.00 | infobox |
| Petr | related to Data jmenin | Pavel | 0.60 | section |
| Petr | related to Data jmenin | Peter | 0.60 | section |
| Petr | related to Data jmenin | Pavol | 0.60 | section |
| Petr | related to Data jmenin | Petr Celestýn | 0.60 | section |
| Petr | related to Data jmenin | Petr Damiani | 0.60 | section |
| Petr | related to Data jmenin | Petr Chanel | 0.60 | section |
| Petr | related to Data jmenin | Petr Chrysolog | 0.60 | section |
The concept neighborhoods around Petr bring nearby vocabulary together. In this analysis, examples include Car, Ruský and Osob. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Petr, one of the stronger structural bridges in this analysis connects Petr with Petr v jiných jazycích. 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 Petr to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Petr v jiných jazycích, Významné osoby & Data jmenin, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Petr · CS edition · Analysis: TopicsToTalkAbout