The need for a quantitative approach in historical linguistics has recently been highlighted by Jenset and McGillivray (2017): in this view, the creation of annotated historical corpora is a fundamental aspect. As Lass (2004) has pointed out, a proper historical corpus should be characterized by maximal information preservation, no irreversible editorial intervention, and maximal flexibility. In order to accomplish Lass’s desiderata, the collection of metadata, which help situate the text in its context, and the preservation of philological annotation are of crucial importance for a correct interpretation of language data in historical texts (Curzan 2009, Vazquez and Marques Aguado 2012).

The aim of this workshop is to reflect on the creation and annotation of historical corpora with a particular focus on the preservation of “contextual” information. Topics of interest include, but are not limited to:

  1. Metadata for historical corpora
  2. Preserving philological information in historical corpora
  3. Linguistic annotation of historical corpora
  4. NLP tools for historical corpora
  5. Corpus-based or corpus-driven research with a particular focus on the study of variation

Curzan, Anne, 2009, Historical corpus linguistics and evidence of language change, in Ludeling A., Kyto M., Corpus linguistics. An International Handbook, Berlin, Mouton de Gruyter,  1091-1108.

Jenset, Gard B., McGillivray Barbara, 2017, Quantitative Historical Linguistics, Oxford, Oxford University Press.

Lass, Roger, 2004, Ut custodiant litteras: Editions, Corpora and Witnesshood, in Dossena M., Lass R. (eds.)  Methods and data in English historical dialectology, Bern, Peter Lang, 21-48.

Vazquez, Nila, Marquez Aguado, Teresa, 2012, Editing the Medieval Manuscript in its Social Context, in Hernandez Campoy L.M., Conde-Silvestre J.C. (eds) The Handbook of Historical Sociolinguistics, Oxford, Wiley-Blackwell, 123-139.

Invited Speakers

Maarten Janssen, University of Coimbra

Joanna Kopaczyk, University of Glasgow

Achim Stein, University of Stuttgart

Abstract submission

Abstracts of no more than 500 words (excluding references) should be submitted through Easy Abstracts (EasyAbs) at

The deadline for abstract submission is 15th November 2018. Notification of acceptance will be given no later than 31th December 2018.