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Euroduplex: History, Regions & Companies
Avelia Euroduplex, more commonly known simply as Euroduplex or TGV 2N2 in France, is a high-speed double-decker train manufactured by Alstom. It is primarily operated by the French national railway company SNCF, and also in operation with the Moroccan national railway company ONCF. It is the 3rd generation of the TGV Duplex.
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Euroduplex topic overview
The analysis highlights History, Regions and Companies as prominent areas in the source structure around Euroduplex.
Related topics
79
Source areas
4
Connected nodes
83
Extracted relationships
101
Concept neighborhoods
18
Bridge connections
83
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.
Operators · 62 topics
Overview · 12 topics
Description · 4 topics
History · 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.
Power car: 22.15 m (72 ft 8 in) End car: 21.845 m (71 ft 8.0 in) Intermediate car: 18.7 m (61 ft 4 in)
Constructed
2011–2023
Coupling system
Scharfenberg
Current collection
Pantograph
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 Euroduplex 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 Euroduplex shows recurring relationship patterns in the source. For example, Euroduplex → Africa, Alstom, Alstom Transport, At, Bordeaux, Casablanca, During, February, France, French, French President Emmanuel Macron, In December, January, July, June, Kenitra, King Mohammed VI, La Rochelle, LGV, May Another extracted example is Euroduplex → Alleo Frankfurt, Alleo Paris-Est, Basel, December, January, LGV East Europe, LGV Rhin-Rhône, Lyon, Lyon-Part-Dieu, Lyria, Lyria Paris-Gare, Marseille, Mediterranean, Munich, Rhine-Rhône, Since, Strasbourg, Stuttgart, TGV POS, Zürich. Use these groups to spot repeated connection types before inspecting the individual relationships.
Euroduplex
Top relations
related to ONCF· 31
Euroduplex → Africa, Alstom, Alstom Transport, At, Bordeaux, Casablanca, During, February, France, French, French President Emmanuel Macron, In December, January, July, June, Kenitra, King Mohammed VI, La Rochelle, LGV, May
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 101 structured relationships around Euroduplex. Examples in this analysis include Euroduplex → Braking systems → Regenerative and pneumatic and Euroduplex → Capacity → 509 seats (SNCF, 55 trainsets) 556 seats (SNCF, 67 trainsets) 533 seats (ONCF). 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 Euroduplex bring nearby vocabulary together. In this analysis, examples include Tgv, High-speed and Oncf. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Euroduplex
Tgv
High-speed
Oncf
Systems
Also
Commercial
Sets
Sncf
Citation
Lgv
Line
Needed
euroduplex
Tgv
High-speed
Oncf
Systems
Also
Commercial
Sets
Sncf
Citation
Lgv
Line
Needed
alstom
Train
Lgv
Citation
Needed
High-speed
First
Avelia
Two
Trains
Sncf
Dasye
Line
tgv duplex
Duplex
Tgv
Dasye
3ufc
Services
Citation
Needed
Trains
Train
Also
Lgv
Two
sncf tgv pos
Duplex
Dasye
Citation
Needed
Services
Trains
Train
Also
3ufc
Lgv
Numbered
Sets
avelia horizon
High-speed
Type
3ufc
Sncf
Citation
Needed
Alstom
Euroduplex
Train
Oncf
Systems
Tgv
kenitra–tangier high-speed rail line
Line
Oncf
Train
Moroccan
Africa
First
Company
Sets
Sncf
Citation
Dasye
Needed
high-speed
Line
Train
Moroccan
Africa
Oncf
First
Company
Sets
Sncf
Citation
Dasye
Needed
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 Euroduplex, one of the stronger structural bridges in this analysis connects Euroduplex with Operators. 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.
Euroduplex
Nodes84
Edges83
Triples101
Avg. degree1.98
Density0.02381
Components1
Source & methodology
TTTA analyzes the structure around Euroduplex to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Regions & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
