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Nightwork: Historie, Vedlejší aktivity & Video
Nightwork byla převážně česky zpívající hudební skupina, která vznikla jako záminka k záškoláctví jejich zakladatelů Františka Soukupa a Emila Kopty. Název vznikl anglickým překladem slov „noční práce“ a vyjadřuje tak časový původ její hudební tvorby. Pravděpodobně méně známé, avšak původní jméno NightWork, postupně zastínilo zjednodušené označení.
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Nightwork topic overview
The analysis highlights Historie, Vedlejší aktivity and Video as prominent areas in the source structure around Nightwork.
Related topics
110
Source areas
6
Connected nodes
116
Extracted relationships
66
Concept neighborhoods
17
Bridge connections
116
What this topic covers Research coverage
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.
Historie · 43 topics
Overview · 30 topics
Vedlejší aktivity · 20 topics
Video · 12 topics
Ocenění · 3 topics
Odkazy · 2 topics
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.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Aktivní roky
2006 – 2013
Ocenění
Cena Anděl za Skupinu roku (2010)
Původ
Praha, Česko
Vydavatel
On Air music
Web
www.nightwork.cz
Žánry
Pop music, Funk, Alternativní rock
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
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.
How Nightwork connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Nightwork shows recurring relationship patterns in the source. For example, Nightwork → Alice Nellis, Běh, Crowd Surfing, Darkwerk, DVD, Haiti, Homo, Incheba, Josefu Váňovi, Nescafé, Nightworki, NYDRLE, Ogilvy, Panic, Paraple, Partička, Pepsi, PEPSICO CZ, Prachy, PREZIDYK Another extracted example is Nightwork → Andělská, Cool Driver, Crowd Surfing, EURO, Globální, Hradu, Kravatatzi, Miroslav Mirčev, Mája, Nakoplá, Panáčky, Pepsi, PEPSICO CZ, Tancuj, Tepláky, Vánoční. Use these groups to spot repeated connection types before inspecting the individual relationships.
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 66 structured relationships around Nightwork. Examples in this analysis include Nightwork → Aktivní roky → 2006 – 2013 and Nightwork → Ocenění → Cena Anděl za Skupinu roku (2010). The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Nightwork
Aktivní roky
2006 – 2013
1.00
infobox
Nightwork
Ocenění
Cena Anděl za Skupinu roku (2010)
1.00
infobox
Nightwork
Původ
Praha, Česko
1.00
infobox
Nightwork
Vydavatel
On Air music
1.00
infobox
Nightwork
Web
www.nightwork.cz
1.00
infobox
Nightwork
Žánry
Pop music, Funk, Alternativní rock
1.00
infobox
Nightwork
related to Externí odkazy
Seznam
0.60
section
Nightwork
related to Externí odkazy
Souborném
0.60
section
Nightwork
related to Externí odkazy
Nightworkwww
0.60
section
Nightwork
related to Externí odkazy
FacebookuČT Live
0.60
section
Nightwork
related to Externí odkazy
Incheba
0.60
section
Nightwork
related to Externí odkazy
HAITI
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Nightwork bring nearby vocabulary together. In this analysis, examples include Dyk, Vojtěch and Františka. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Nightwork
Dyk
Vojtěch
Františka
Soukupa
Signál
Tepláky
Skupina
Aneb
Jakub
Kroky
Prachař
Skladba
nightwork
Dyk
Vojtěch
Františka
Soukupa
Signál
Tepláky
Skupina
Aneb
Jakub
Kroky
Prachař
Skladba
kapela
Videoklip
Písně
Roku
Nightwork
Skupina
Kategorii
Místo
Zpěvák
Aneb
Kroky
Skladba
Dyk
františka soukupa
Soukupa
Aneb
Kroky
Nightwork
Tepláky
Skladba
Soukup
Dyk
Vojtěch
Roku
Hudební
Jako
vojtěch dyk
Vojtěch
Globální
Oteplování
Zpěvák
Nightwork
Signál
Tepláky
Jakub
Kroky
Prachař
Skladba
Soukup
veselé velikonoce s nightwork
Dyk
Vojtěch
Františka
Soukupa
Signál
Tepláky
Skupina
Aneb
Jakub
Kroky
Prachař
Skladba
čtení pomáhá: vojtěch dyk jako mistr čti-wo
Vojtěch
Globální
Oteplování
Zpěvák
Nightwork
Signál
Tepláky
Jakub
Kroky
Prachař
Skladba
Soukup
globální oteplování
Oteplování
Dyk
Vojtěch
Píseň
Zpěvák
Signál
Tepláky
Mája
Písně
Nightwork
Kategorii
Skupina
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Nightwork, one of the stronger structural bridges in this analysis connects Nightwork 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.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Nightwork
Nodes117
Edges116
Triples66
Avg. degree1.98
Density0.017094
Components1
Source & methodology
TTTA analyzes the structure around Nightwork to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Historie, Vedlejší aktivity & Video, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
