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Swabi (Pashto: صوابۍ; Urdu: صوابی) is a city in the Khyber Pakhtunkhwa province of Pakistan. It is located near the bank of the Indus River. It is the 73rd largest city of Pakistan and eighth largest in the province in Khyber Pakhtunkhwa.[citation needed] Swabi is also a major city in the Mardan Division, where it is the second-largest city.[citation needed]
The analysis highlights Community, Notable people and Visit as prominent areas in the source structure around Swabi.
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 Swabi shows recurring relationship patterns in the source. For example, Swabi → Dawood Khan Yousafzai, Former Pakistani Senator, Former Speaker, Jamaat-e-Islami, Leader, MMA World, National Assembly, Pakistan, Pakistan Tehreek-e-Insaf, Pakistani, Qaiser, Save Gaza, SwabiMushtaq Ahmad Khan Another extracted example is Swabi → According, Between, Census, However, Khyber Pakhtunkhwa, Pakistan, Pashtuns, The, These, Yusufzai. 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.
pakistan city khyber pakhtunkhwa province average population climate located 73rd temperature month notable 12 district tehsil time pashto urdu inhabitants
TTTA extracted 49 structured relationships around Swabi. Examples in this analysis include Swabi → Calling code → +92 938 and Swabi → Country → Pakistan. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Swabi | Calling code | +92 938 | 1.00 | infobox |
| Swabi | Country | Pakistan | 1.00 | infobox |
| Swabi | District | Swabi | 1.00 | infobox |
| Swabi | Elevation | 340 m (1,120 ft) | 1.00 | infobox |
| Swabi | Province | Khyber Pakhtunkhwa | 1.00 | infobox |
| Swabi | Tehsil | Swabi | 1.00 | infobox |
| Swabi | Time zone | UTC+5 (PST) | 1.00 | infobox |
| Swabi | • Rank | 73rd, Pakistan 8th, Khyber Pakhtunkhwa | 1.00 | infobox |
| Swabi | • Total | 156,496 | 1.00 | infobox |
| Swabi | related to Climate | With | 0.60 | section |
| Swabi | related to Climate | Köppen Cwa | 0.60 | section |
| Swabi | related to Climate | The | 0.60 | section |
The concept neighborhoods around Swabi bring nearby vocabulary together. In this analysis, examples include Climate, Pakistan and Population. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Swabi, one of the stronger structural bridges in this analysis connects Swabi with Notable people. 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 Swabi to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Community, Notable people & Visit, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Swabi · EN edition · Analysis: TopicsToTalkAbout