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Johan Sverdrup (30. července 1816 Sem – 17. února 1892 Oslo) byl norský politik, představitel liberální strany Venstre, jejímž zakladatelem a prvním předsedou byl. Stal se čtvrtým premiérem Norska v letech 1884–1889 a byl prvním norským premiérem, který byl demokraticky zvolen. Během svého premiérského mandátu vedl souběžně i několik resortů: byl…
The analysis highlights Život, Odkazy and Overview as prominent areas in the source structure around Johan Sverdrup.
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 Johan Sverdrup shows recurring relationship patterns in the source. For example, Johan Sverdrup → Obrázky, Wikimedia Commons Another extracted example is Johan Sverdrup → Oselská katedrální škola. 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.
sverdrup stortingu roce venstre jeho strany strana norsku 30 července 17 února 1889 let 1816 1892 politik jako král to
TTTA extracted 15 structured relationships around Johan Sverdrup. Examples in this analysis include Johan Sverdrup → Alma mater → Oselská katedrální škola and Johan Sverdrup → Funkce → Mayor of Larvik (1850) člen norského parlamentu (1851–1853) Mayor of Larvik (1852–1853) člen norského parlamentu (1854–1856) Mayor of Larvik (1856) … více na Wikidatech. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Johan Sverdrup | Alma mater | Oselská katedrální škola | 1.00 | infobox |
| Johan Sverdrup | Funkce | Mayor of Larvik (1850) člen norského parlamentu (1851–1853) Mayor of Larvik (1852–1853) člen norského parlamentu (1854–1856) Mayor of Larvik (1856) … více na Wikidatech | 1.00 | infobox |
| Johan Sverdrup | Místo pohřbení | hřbitov Vår Frelsers | 1.00 | infobox |
| Johan Sverdrup | Narození | 30. července 1816 Tønsberg | 1.00 | infobox |
| Johan Sverdrup | Nábož. vyznání | Norská církev | 1.00 | infobox |
| Johan Sverdrup | Občanství | Norsko | 1.00 | infobox |
| Johan Sverdrup | Ocenění | Řád svatého Olafa (1885) Velkokříž za námořní zásluhy s bílým odznakem (1886) | 1.00 | infobox |
| Johan Sverdrup | Politická strana | Venstre | 1.00 | infobox |
| Johan Sverdrup | Povolání | politik, redaktor, novinář a advokát | 1.00 | infobox |
| Johan Sverdrup | Příbuzní | Harald Ulrik Sverdrup (bratr) William Sverdrup | 1.00 | infobox |
| Johan Sverdrup | Rodiče | Jacob Sverdrup | 1.00 | infobox |
| Johan Sverdrup | Úmrtí | 17. února 1892 (ve věku 75 let) Christiania | 1.00 | infobox |
The concept neighborhoods around Johan Sverdrup bring nearby vocabulary together. In this analysis, examples include Jeho, Commons and Politik. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Johan Sverdrup, one of the stronger structural bridges in this analysis connects Johan Sverdrup with Život. 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 Johan Sverdrup to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Život, Odkazy & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Johan Sverdrup · CS edition · Analysis: TopicsToTalkAbout