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The Hase (German pronunciation: ⓘ) is a 169.7-kilometre-long (105.4 mi) river of Lower Saxony, Germany. It is a right tributary of the Ems, but part of its flow goes to the Else, that is part of the Weser basin. Its source is in the Teutoburg Forest, south-east of Osnabrück, on the north slope of the 307-metre-high (1,007 ft) Hankenüll hill.
The analysis highlights Art, Towns and Weser-Ems watershed as prominent areas in the source structure around Hase.
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 Hase shows recurring relationship patterns in the source. For example, Hase → After, Else, Ems, Gesmold, Herford, Kirchlengern, Melle, Meppen, One, Osnabrück, The Werre, Two, Werre, Weser, Wiehengebirge Another extracted example is Hase → Bersenbrück, Bramsche, Essen, Haselünne, Herzlake, Löningen, Meppen (mouth), Osnabrück, Quakenbrück, Wellingholzhausen (source). 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.
osnabrück ems else mw-parser-output mi lower saxony basin north meppen melle germany flow references weser font-size 85 169 105 river
TTTA extracted 51 structured relationships around Hase. Examples in this analysis include Hase → Basin size → 3,116 km2 (1,203 sq mi) and Hase → Cities → Meppen (mouth). The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Hase | Basin size | 3,116 km2 (1,203 sq mi) | 1.00 | infobox |
| Hase | Cities | Meppen (mouth) | 1.00 | infobox |
| Hase | Cities | Haselünne | 1.00 | infobox |
| Hase | Cities | Herzlake | 1.00 | infobox |
| Hase | Cities | Löningen | 1.00 | infobox |
| Hase | Cities | Essen | 1.00 | infobox |
| Hase | Cities | Quakenbrück | 1.00 | infobox |
| Hase | Cities | Bersenbrück | 1.00 | infobox |
| Hase | Cities | Bramsche | 1.00 | infobox |
| Hase | Cities | Osnabrück | 1.00 | infobox |
| Hase | Cities | Wellingholzhausen (source) | 1.00 | infobox |
| Hase | Country | Germany | 1.00 | infobox |
| Hase | Etymology | haswa, germanic for gray | 1.00 | infobox |
| Hase | Length | 169.7 km (105.4 mi) | 1.00 | infobox |
| Hase | Mouth | Ems River | 1.00 | infobox |
| Hase | Progression | .mw-parser-output .tfd-dated{font-size:85%}.mw-parser-output .tfd-default{border-bottom:1px solid var(--border-color-base,#a2a9b1);text-align:center}.mw-parser-output .tfd-tiny{… | 1.00 | infobox |
| Hase | State | Lower Saxony | 1.00 | infobox |
| Hase | • coordinates | .mw-parser-output .geo-default,.mw-parser-output .geo-dms,.mw-parser-output .geo-dec{display:inline}.mw-parser-output .geo-nondefault,.mw-parser-output .geo-multi-punct,.mw-pars… | 1.00 | infobox |
| Hase | • coordinates | 52°41′28″N 7°17′48″E / 52.69111°N 7.29667°E / 52.69111; 7.29667 | 1.00 | infobox |
| Hase | • elevation | 165 m (541 ft) | 1.00 | infobox |
| Hase | • elevation | 15 m (49 ft) | 1.00 | infobox |
| Hase | • location | Melle-Wellingholzhausen, Teutoburg Forest | 1.00 | infobox |
| Hase | • location | Meppen | 1.00 | infobox |
| Hase | • right | Südradde, Mittelradde | 1.00 | infobox |
The concept neighborhoods around Hase bring nearby vocabulary together. In this analysis, examples include Flows, Lower and Meppen. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Hase, one of the stronger structural bridges in this analysis connects Hase with Towns. 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 Hase to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Towns & Weser-Ems watershed, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Hase · EN edition · Analysis: TopicsToTalkAbout