Historical corpora for historical research

Sketch Engine helps historians analyse historical texts using corpus tools. Search for words and phrases in context, examine their frequency and compare language across periods, authors and genres.

Build your own historical corpus

Upload historical texts in formats such as TXT, PDF and DOC to create a searchable corpus. You can also collect texts from selected websites.

Divide your corpus into subcorpora to focus on a particular period, author or genre.

Explore historical corpora

Sketch Engine includes historical corpora in several languages. The examples below cover literary works, dialogues, newspapers and parliamentary proceedings.

Historical corpora available in Sketch Engine
Corpus Language Period Open in Sketch Engine
Corpus of English Dialogues English 1560–1760 Search ↗
Historical English collection: EEBO, ECCO and Evans English 1473–1820 Search ↗
GerManC: Historical Corpus of German Newspapers German 1650–1800 Search ↗
Old and Middle French (BFM 2022) French 945–1497 Search ↗
Penn Historical Corpora English 1150–1900 Search ↗
Polish Parliamentary Corpus (PPC) Polish 1919–2020 Search ↗
DraCor drama corpora 14 languages and dialects 472 BC–AD 2017 Choose corpus ↗
LatinISE corpus Latin 8th century BC–21st century AD Search ↗

Sketch Engine is also being used in the ChartEx project which applies text mining methods to medieval Latin charters. It will make the corpora publicly available through Sketch Engine as the project proceeds.

Access to some corpora requires permission from the copyright holder

This applies to English Dialogues and the Penn Historical Corpora.

Reference

Adam Kilgarriff, Miloš Husák and Robyn Woodrow (2012). The Sketch Engine as infrastructure for historical corpora. In Jeremy Jancsary (ed.). Empirical Methods in Natural Language Processing; Proceedings of the Conference on Natural Language Processing 2012, pp. 351–356

Barbara McGillivray and Adam Kilgarriff (2012). Tools for historical corpus research, and a corpus of Latin (presentation). In New Methods in Historical Corpus Linguistics 3, Germany, 2013, pp. 247–255.