Encoding verse texts

David H Chisholm, David Robey

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)99-111
Number of pages13
JournalComputers and the Humanities
Volume29
Issue number2
DOIs
StatePublished - Mar 1995

Fingerprint

group work
opposition
linguistics
examination
interpretation
Verse
Encoding
Tagging
Feature Structures
Uniformity
Specificity
Verse Form
Fidelity
Prose
English Verse
Rhyme
Generality
Transcription

Keywords

  • poetry
  • SGML
  • tagging
  • TEI
  • text encoding
  • verse

ASJC Scopus subject areas

  • Linguistics and Language

Cite this

Encoding verse texts. / Chisholm, David H; Robey, David.

In: Computers and the Humanities, Vol. 29, No. 2, 03.1995, p. 99-111.

Research output: Contribution to journalArticle

Chisholm, David H ; Robey, David. / Encoding verse texts. In: Computers and the Humanities. 1995 ; Vol. 29, No. 2. pp. 99-111.
@article{2d7b33c562f3412b9c2309bd2d4c10ee,
title = "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.",
keywords = "poetry, SGML, tagging, TEI, text encoding, verse",
author = "Chisholm, {David H} and David Robey",
year = "1995",
month = "3",
doi = "10.1007/BF01830704",
language = "English (US)",
volume = "29",
pages = "99--111",
journal = "Language Resources and Evaluation",
issn = "1574-020X",
publisher = "Springer Netherlands",
number = "2",

}

TY - JOUR

T1 - Encoding verse texts

AU - Chisholm, David H

AU - Robey, David

PY - 1995/3

Y1 - 1995/3

N2 - 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.

AB - 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.

KW - poetry

KW - SGML

KW - tagging

KW - TEI

KW - text encoding

KW - verse

UR - http://www.scopus.com/inward/record.url?scp=34248825441&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34248825441&partnerID=8YFLogxK

U2 - 10.1007/BF01830704

DO - 10.1007/BF01830704

M3 - Article

AN - SCOPUS:34248825441

VL - 29

SP - 99

EP - 111

JO - Language Resources and Evaluation

JF - Language Resources and Evaluation

SN - 1574-020X

IS - 2

ER -