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Walensee: Geography, Settlements and transportation & Name
The Walensee (German pronunciation: ⓘ), also known as Lake Walen and Lake Walenstadt (after Walenstadt), is one of the larger lakes in Switzerland. Located in the east of the country, about two thirds of its area are in the canton of St. Gallen and about one third in the canton of Glarus.
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Walensee topic overview
The analysis highlights Geography, Settlements and transportation and Name as prominent areas in the source structure around Walensee.
Related topics
59
Source areas
6
Connected nodes
65
Extracted relationships
68
Concept neighborhoods
23
Bridge connections
65
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.
Geography · 27 topics
Settlements and transportation · 16 topics
Overview · 7 topics
Name · 5 topics
Arts · 3 topics
Gallery · 1 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.
Location
St. Gallen, Glarus
Average depth
104.7 m (344 ft)
Basin countries
Switzerland
Islands
Schnittlauchinsel
Max. depth
151 m (495 ft)
Primary inflows
Linth (Escherkanal), Seez, Murgbach
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 Walensee 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 Walensee shows recurring relationship patterns in the source. For example, Walensee → A3, Apart, At Betlis, Commercial, Flumserberg, Kerenzerberg, Mols, Murg, Mühlehorn, Oberterzen, Quinten, Route, Sargans, There, To, Unterterzen, Walensee-Schifffahrt, Walenstadt, Weesen, Ziegelbrücke Another extracted example is Walensee → Appenzell Alps, Glarus Alps, It, Lake Zurich, Linth, Maag, Murgbach, Obersee, Rinquelle, Seez, The, The Schnittlauchinsel, The Seerenbach Falls, Until, Ziegelbrücke. 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 68 structured relationships around Walensee. Examples in this analysis include Walensee → Average depth → 104.7 m (344 ft) and Walensee → Basin countries → Switzerland. The table shows each extracted connection, where it came from and its confidence.
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 Walensee bring nearby vocabulary together. In this analysis, examples include Linth, Switzerland and Canal. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Walensee
Linth
Switzerland
Canal
Schnittlauchinsel
West
Canton
Lakes
Quarten
Alps
Near
Gallen
Located
walensee
Linth
Switzerland
Canal
Schnittlauchinsel
West
Canton
Lakes
Quarten
Alps
Near
Gallen
Located
switzerland
Quarten
Walensee
Canal
Schnittlauchinsel
Gallen
Located
West
Glarus
Linth
Murg
Weesen
Canton
canton
St
East
Gallen
Located
Glarus
Settlements
Alps
Walensee
Mw-parser-output
Switzerland
Walenstadt
Depth
st. gallen
Glarus
Located
Switzerland
St
Depth
German
Murgbach
One
Quarten
Seez
Settlements
Surface
glarus
Alps
Located
Switzerland
St
Depth
Murgbach
One
Quarten
Seez
Settlements
Surface
Walensee
glarus alps
Alps
Glarus
Located
Canton
German
Switzerland
St
East
North
Walensee
Depth
Gallen
lake zurich
Walenstadt
South
Murg
Walensee
Mw-parser-output
Unterterzen
Linth
Weesen
Lakes
References
Walen
Canal
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 Walensee, one of the stronger structural bridges in this analysis connects Walensee with Geography. 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.
Walensee
Nodes66
Edges65
Triples68
Avg. degree1.97
Density0.030303
Components1
Source & methodology
TTTA analyzes the structure around Walensee to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Geography, Settlements and transportation & Name, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
