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Michael Fred Phelps (* 30. června 1985 Baltimore, Maryland, USA) je americký plavec, držitel rekordního počtu 28 olympijských medailí, z toho 23 zlatých. Rekordem je i 13 zlatých a celkem 16 medailí z individuálních soutěží. Ziskem osmi zlatých medailí na Letních olympijských hrách 2008 v Pekingu pokořil rekord jiného amerického plavce Marka Spitze…
The analysis highlights Výsledky plavecké kariéry, Overview and Olympiáda v Pekingu as prominent areas in the source structure around Michael Phelps.
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 Michael Phelps shows recurring relationship patterns in the source. For example, Michael Phelps → FINA, LOH, Michael Phelps Archivováno, Nejlepší, Obrázky, Olympedia, Phelps, Stream, USA, Wayback Machine, Wikimedia Commons Zpráva Michael, WikizpráváchMichael Phelps Another extracted example is Michael Phelps → 30. června 1985 (41 let). 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.
phelps 2016 zlatých medailí rekord motýlek 200 michael polohový závod 2008 2012 loh pekingu den her olympijských volný způsob světový
TTTA extracted 20 structured relationships around Michael Phelps. Examples in this analysis include Michael Phelps → Datum narození → 30. června 1985 (41 let) and Michael Phelps → Disciplína → volný způsob, motýlek, polohový závod, znak. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Michael Phelps | Datum narození | 30. června 1985 (41 let) | 1.00 | infobox |
| Michael Phelps | Disciplína | volný způsob, motýlek, polohový závod, znak | 1.00 | infobox |
| Michael Phelps | Hmotnost | 88 kg | 1.00 | infobox |
| Michael Phelps | Místo narození | Baltimore, Maryland Spojené státy americké Spojené státy americké | 1.00 | infobox |
| Michael Phelps | Stát | USA | 1.00 | infobox |
| Michael Phelps | Výška | 193 cm | 1.00 | infobox |
| Michael Phelps | Účast na LOH | 2000, 2004, 2008, 2012, 2016 | 1.00 | infobox |
| Michael Phelps | related to Externí odkazy | Obrázky | 0.60 | section |
| Michael Phelps | related to Externí odkazy | Wikimedia Commons Zpráva Michael | 0.60 | section |
| Michael Phelps | related to Externí odkazy | Phelps | 0.60 | section |
| Michael Phelps | related to Externí odkazy | WikizpráváchMichael Phelps | 0.60 | section |
| Michael Phelps | related to Externí odkazy | Olympedia | 0.60 | section |
The concept neighborhoods around Michael Phelps bring nearby vocabulary together. In this analysis, examples include Phelps, Baltimore and Maryland. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Michael Phelps, one of the stronger structural bridges in this analysis connects Michael Phelps with Overview. 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 Michael Phelps to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Výsledky plavecké kariéry, Overview & Olympiáda v Pekingu, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Michael Phelps · CS edition · Analysis: TopicsToTalkAbout