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Thame (/teɪm/ ⓘ) is a market town and civil parish in Oxfordshire, England. It is located about 13 miles (21 km) east of the city of Oxford, 10 miles (16 km) south-west of Aylesbury and 40 miles (64 km) north-west of London. It derives its name from the River Thame, which flows along the north side of the town and forms part of the county border with…
The analysis highlights History, Culture, Economy and Art as prominent areas in the source structure around Thame.
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 Thame shows recurring relationship patterns in the source. For example, Thame → Andy Gibb, Austin, BBC, Bee Gees, Bruce, Catholic, Church, Coldcut, Cuttle Brook House, Daniel Gruchy, Dwina Murphy-Gibb, England, English, Father Randolph Traill, Gavin, Gavin Free, Harman Grisewood, His, Howard Goodall, In Another extracted example is Thame → Archaeology, Archibald Constable, Aston, Bond, Co, County, Dent, Dorchester Hundreds, Ecclesiastical History, Field Series, Historical Research, History, Institute, ISBN, James, Lobel, London, Mary, Michael, Oxford. 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.
town oxford century parish county south oxfordshire john church built local london house early gothic north district england prebendal council
TTTA extracted 245 structured relationships around Thame. Examples in this analysis include Thame → Ambulance → South Central and Thame → Area → 12.67 km2 (4.89 sq mi). The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Thame | Ambulance | South Central | 1.00 | infobox |
| Thame | Area | 12.67 km2 (4.89 sq mi) | 1.00 | infobox |
| Thame | Civil parish | Thame | 1.00 | infobox |
| Thame | Country | England | 1.00 | infobox |
| Thame | Dialling code | 01844 | 1.00 | infobox |
| Thame | District | South Oxfordshire | 1.00 | infobox |
| Thame | Fire | Oxfordshire | 1.00 | infobox |
| Thame | OS grid reference | SP710060 | 1.00 | infobox |
| Thame | Police | Thames Valley | 1.00 | infobox |
| Thame | Population | 13,273 (2021 Census) | 1.00 | infobox |
| Thame | Post town | THAME | 1.00 | infobox |
| Thame | Postcode district | OX9 | 1.00 | infobox |
| Thame | Region | South East | 1.00 | infobox |
| Thame | Shire county | Oxfordshire | 1.00 | infobox |
| Thame | Sovereign state | United Kingdom | 1.00 | infobox |
| Thame | UK Parliament | Henley and Thame | 1.00 | infobox |
| Thame | Website | Thame Town Council | 1.00 | infobox |
| Thame | • Density | 1,048/km2 (2,710/sq mi) | 1.00 | infobox |
| Thame | • London | 40 miles (64 km) | 1.00 | infobox |
The concept neighborhoods around Thame bring nearby vocabulary together. In this analysis, examples include Town, Council and Oxford. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Thame, one of the stronger structural bridges in this analysis connects Thame 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 Thame to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Culture, Economy & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Thame · EN edition · Analysis: TopicsToTalkAbout