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Kastav (italsky Castua) je město v Chorvatsku v Přímořsko-gorskokotarské župě. Nachází se asi 6 km severozápadně od Rijeky. Ve městě žije přibližně 10 tisíc obyvatel, díky čemuž je druhým největším městem Přímořsko-gorskokotarské župy (po Rijece), avšak je i přes svoji samostatnost de facto předměstím Rijeky.
The analysis highlights Historie, Administrativní dělení and Název as prominent areas in the source structure around Kastav.
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 Kastav shows recurring relationship patterns in the source. For example, Kastav → Brnčići, Do, Jelovičani, Jurčići, Kastavu, Rubeši, Spinčići, Trinajstići Another extracted example is Kastav → Dále, Jeleny Križarice, Kastavu, Trojice. 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.
město rijeky obyvatel města zde commons přímořsko-gorskokotarské 2011 chorvatsko 10 administrativní dělení brnčići ćikovići jelovičani jurčići rubeši spinčići trinajstići kastavu
TTTA extracted 36 structured relationships around Kastav. Examples in this analysis include Kastav → Administrativní dělení → Brnčići, Ćikovići, Jelovičani, Jurčići, Kastav, Rubeši, Spinčići, Trinajstići and Kastav → Adresa obecního úřadu → Trg svete Lucije 1, 51215 Kastav. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Kastav | Administrativní dělení | Brnčići, Ćikovići, Jelovičani, Jurčići, Kastav, Rubeši, Spinčići, Trinajstići | 1.00 | infobox |
| Kastav | Adresa obecního úřadu | Trg svete Lucije 1, 51215 Kastav | 1.00 | infobox |
| Kastav | Etnické složení | Chorvati | 1.00 | infobox |
| Kastav | Hustota zalidnění | 894,9 obyv./km² | 1.00 | infobox |
| Kastav | Nadmořská výška | 378 m n. m. | 1.00 | infobox |
| Kastav | Náboženské složení | křesťané | 1.00 | infobox |
| Kastav | Oficiální web | www.kastav.hr | 1.00 | infobox |
| Kastav | Označení vozidel | RI | 1.00 | infobox |
| Kastav | Počet obyvatel | 10 202 (2021) | 1.00 | infobox |
| Kastav | PSČ | 51215 | 1.00 | infobox |
| Kastav | Region | Gorski Kotar | 1.00 | infobox |
| Kastav | Rozloha | 11,40 km² | 1.00 | infobox |
| Kastav | Souřadnice | 45°22′21″ s. š., 14°20′56″ v. d. | 1.00 | infobox |
| Kastav | Starosta | Matej Mostarac | 1.00 | infobox |
| Kastav | Status | město | 1.00 | infobox |
| Kastav | Stát | Chorvatsko Chorvatsko | 1.00 | infobox |
| Kastav | Telefonní předvolba | 051 | 1.00 | infobox |
| Kastav | Župa | Přímořsko-gorskokotarská | 1.00 | infobox |
The concept neighborhoods around Kastav bring nearby vocabulary together. In this analysis, examples include Město, Commons and Wikimedia. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Kastav, one of the stronger structural bridges in this analysis connects Kastav with Historie. 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 Kastav to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Historie, Administrativní dělení & Název, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Kastav · CS edition · Analysis: TopicsToTalkAbout