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Sintra (/ˈsɪntrə, ˈsiːntrə/, Portuguese: ⓘ), officially the Town of Sintra (Portuguese: Vila de Sintra), is a town and municipality in the Greater Lisbon region of Portugal, located on the Portuguese Riviera. The population of the municipality in 2021 was 385,654, in an area of 319.23 square kilometres (123.26 sq mi). Sintra is one of the most urbanized…
The analysis highlights History, Geography, Culture and Politics as prominent areas in the source structure around Sintra.
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 Sintra shows recurring relationship patterns in the source. For example, Sintra → Afonso Henriques, Almada, Arrabalde, But, Canaferrim, Castle, Christian, Christians, Church, Colares, Colares River, Count Henry, Crusader, Crusaders, Gualdim Pais, Holy Land, In July, It, January, King Denis Another extracted example is Sintra → Acer, Alnus, Although, Arbutus, Atlantic, Bay, Cabo, Corylus, Crataegus, Due, European, For, Frangula, Fraxinus, Grey, Ilex, In, Italian, Kermes, Laurus. 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.
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TTTA extracted 390 structured relationships around Sintra. Examples in this analysis include Sintra → Area → 946 ha (2,340 acres) and Sintra → Area code → 219. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Sintra | Area | 946 ha (2,340 acres) | 1.00 | infobox |
| Sintra | Area code | 219 | 1.00 | infobox |
| Sintra | Country | Portugal | 1.00 | infobox |
| Sintra | Criteria | Cultural: ii, iv, v | 1.00 | infobox |
| Sintra | District | Lisbon | 1.00 | infobox |
| Sintra | Elevation | 175 m (574 ft) | 1.00 | infobox |
| Sintra | Inscription | 1995 (19th Session) | 1.00 | infobox |
| Sintra | Lowest elevation | 0 m (0 ft) | 1.00 | infobox |
| Sintra | Metropolitan area | Lisbon | 1.00 | infobox |
| Sintra | Official name | Cultural Landscape of Sintra | 1.00 | infobox |
| Sintra | Parishes | 11 (list) | 1.00 | infobox |
| Sintra | Patron | São Pedro | 1.00 | infobox |
| Sintra | Postal code | 2714 | 1.00 | infobox |
| Sintra | Reference | 723 | 1.00 | infobox |
| Sintra | Region | Lisbon | 1.00 | infobox |
| Sintra | Time zone | UTC+00:00 (WET) | 1.00 | infobox |
| Sintra | Website | http://www.cm-sintra.pt body.skin-minerva .mw-parser-output .infobox table{display:table}body.skin-minerva .mw-parser-output .infobox caption{display:table-caption} | 1.00 | infobox |
| Sintra | • Density | 1,183.6/km2 (3,065.5/sq mi) | 1.00 | infobox |
| Sintra | • President | Marco Almeida (PSD) | 1.00 | infobox |
| Sintra | • Summer (DST) | UTC+01:00 (WEST) | 1.00 | infobox |
| Sintra | • Total | 319.23 km2 (123.26 sq mi) | 1.00 | infobox |
| Sintra | • Total | 377,835 | 1.00 | infobox |
The concept neighborhoods around Sintra bring nearby vocabulary together. In this analysis, examples include De, Mountains and Town. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Sintra, one of the stronger structural bridges in this analysis connects Sintra with History. 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 Sintra to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Geography, Culture & Politics, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Sintra · EN edition · Analysis: TopicsToTalkAbout