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Babalet: Historie, Diskografie & Overview
Babalet byla česká hudební skupina, která vznikla v roce 1984 na popud hudebníka Aleše Drvoty. Kapelu s Drvotou založili Ivan Pavlů, Karel Babuljak, Jiří Charypar, Jan Šimek a Jiří Šíma. Původně hráli rockové skladby a reggae a po obměně kapely v roce 1985 se zaměřili výhradně na reggae. Později ve snaze o větší tanečnost svou hudbu obohatili o africké…
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Babalet topic overview
The analysis highlights Historie, Diskografie and Overview as prominent areas in the source structure around Babalet.
Related topics
41
Source areas
3
Connected nodes
44
Extracted relationships
41
Concept neighborhoods
7
Bridge connections
44
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 · 32 topics
Overview · 7 topics
Diskografie · 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
1984–2019
Původ
Praha, Československo
Vydavatelé
Panton, Popron, multiSONic
Žánry
rock, reggae
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 Babalet 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 Babalet shows recurring relationship patterns in the source. For example, Babalet → Aleš Drvota, Babaletu, Boba Marleyho, Ivanem Pavlů, Jana, Jiřího, Jiřího Charypara, Karla Babuljaka, Mama Bubo, Na, Omnibus, Po, Počáteční, Praha Opatov, Premiérový, Santa Monica, Spolu, Velké Británie, Vystoupení Another extracted example is Babalet → Aleš Drvota Live, Best, CD, Che Music Production, Impuls, KMa, Kompilace Rockový, Kytkový, LP, Nola, Panton, Popron, Posvátná, Rasta, SP, Years, Zelená, Zítra. Use these groups to spot repeated connection types before inspecting the individual relationships.
Babalet
Top relations
related to Historie· 19
Babalet → Aleš Drvota, Babaletu, Boba Marleyho, Ivanem Pavlů, Jana, Jiřího, Jiřího Charypara, Karla Babuljaka, Mama Bubo, Na, Omnibus, Po, Počáteční, Praha Opatov, Premiérový, Santa Monica, Spolu, Velké Británie, Vystoupení
related to Diskografie· 18
Babalet → Aleš Drvota Live, Best, CD, Che Music Production, Impuls, KMa, Kompilace Rockový, Kytkový, LP, Nola, Panton, Popron, Posvátná, Rasta, SP, Years, Zelená, Zítra
Aktivní roky· 1
Babalet → 1984–2019
Původ· 1
Babalet → Praha, Československo
Vydavatelé· 1
Babalet → Panton, Popron, multiSONic
Žánry· 1
Babalet → rock, reggae
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
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 41 structured relationships around Babalet. Examples in this analysis include Babalet → Aktivní roky → 1984–2019 and Babalet → Původ → Praha, Československo. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Babalet
Aktivní roky
1984–2019
1.00
infobox
Babalet
Původ
Praha, Československo
1.00
infobox
Babalet
Vydavatelé
Panton, Popron, multiSONic
1.00
infobox
Babalet
Žánry
rock, reggae
1.00
infobox
Babalet
related to Diskografie
Zelená
0.60
section
Babalet
related to Diskografie
Rasta
0.60
section
Babalet
related to Diskografie
Panton
0.60
section
Babalet
related to Diskografie
SP
0.60
section
Babalet
related to Diskografie
Kompilace Rockový
0.60
section
Babalet
related to Diskografie
Posvátná
0.60
section
Babalet
related to Diskografie
Nola
0.60
section
Babalet
related to Diskografie
Impuls
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 Babalet bring nearby vocabulary together. In this analysis, examples include Roce, Koncert and Reggae. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Babalet
Roce
Koncert
Reggae
Karel
Charypar
Babuljak
Aleš
Kumandžas
Malík
Panton
Založili
Švadlena
babalet
Roce
Koncert
Reggae
Karel
Charypar
Babuljak
Aleš
Kumandžas
Malík
Panton
Založili
Švadlena
karel babuljak
Charypar
Kozmor
Karel
Pavlů
Aleš
Reggae
Členové
Ivan
Jan
Jiří
Koncert
Kumandžas
jiří charypar
Jan
Perkuse
Pavlů
Karel
Ivan
Aleš
Charypar
Jiří
Kozmor
Šimsa
Panton
Drvota
reggae
Aleš
Babaletu
Drvota
Roce
Členové
Koncert
Kozmor
Kumandžas
Malík
Panton
Perkuse
Šimsa
panton
Aleš
Perkuse
Drvota
Pavlů
Členové
Kozmor
Kumandžas
Malík
Reggae
Šimsa
Švadlena
Roce
aleše drvoty
Drvoty
Frontmana
Kapely
Roce
Babaletu
Babalet
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 Babalet, one of the stronger structural bridges in this analysis connects Babalet 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.
Babalet
Nodes45
Edges44
Triples41
Avg. degree1.96
Density0.044444
Components1
Source & methodology
TTTA analyzes the structure around Babalet to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Historie, Diskografie & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
