Encoding Verse Texts

Abstract

This article identifies problems and proposes solutions for encoding verse texts in SGML. It is organized around a series of distinctions and oppositions which the TEI Work Group on Verse regard as significant. These include examination of the formal properties which distinguish verse from prose, followed by discussions of (1) text-searching vs analysis, (2) markup vs algorithms, (3) markup vs transcription, (4) uniformity vs choice, (5) specificity vs generality, (6) metrical convention vs linguistic realization, (7) structural vs non-structural divisions and (8) fidelity vs interpretation. Using German and English verse forms as illustrations, the advantages and disadvantages of pre-line tagging, in-line tagging and feature structure analysis are discussed. We suggest that metrical and rhyme conventions always be tagged at the highest possible level of text divisions.

David Chisholm is Professor of German Studies at the University of Arizona. His interests include German lyric poetry and verse drama, metrics and versification, linguistic and computational approaches to literature, and phonological and prosodic aspects of literary style. His publications include “Computer-assisted Research in German Language and Literature” in the German Quarterly (1985), Verskonkordanz zu Goethes “Faust, Erster Teil” (with Stephen P. Sondrup, 1986), “Phonological Patterning in Twentieth Century German Verse and Prose” in Descriptio Linguistica (1986) and “Lexicality and the Versification of Johann Heinrich Voss” in Insights in Germanic Linguistics (1994).

David Robey is Professor of Italian at Manchester University and Dean of the Faculty of Arts. He has worked on Italian Renaissance Humanism, modern literary theory (editor and author with Ann Jefferson of Modern Literary Theory: A Comparative Introduction), and on the computer analysis of medieval and Renaissance narrative poetry. He is currently engaged in a metrical study of the Divine Comedy, and was Chair of the Verse Work Group of the Text Encoding Inititiative.