LERA—an interactive platform for synoptical representations of multiple text witnesses.

In the humanities, text comparison is essential for scholarly editing the traditions of a text with its different witnesses under study. For the computer-aided creation of a critical apparatus, there have been established approaches and tools for many years. However, they mainly focus on subsentence...

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Publicado en:Digital Scholarship in the Humanities Vol. 38; no. 1; pp. 330 - 347
Autores principales: Pöckelmann, Marcus, Medek, André, Ritter, Jörg, Molitor, Paul
Formato: Artículo
Publicado: Oxford University Press / USA Apr2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Pöckelmann, Marcus
          Medek, André
          Ritter, Jörg
          Molitor, Paul
        affil: Martin Luther University Halle-Wittenberg, Computer Science Institute , Germany
      su:
        Records management
        Yiddish language
        Witnesses
        English language
        French language
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          Records management
          Yiddish language
          Witnesses
          English language
          French language
      ab: In the humanities, text comparison is essential for scholarly editing the traditions of a text with its different witnesses under study. For the computer-aided creation of a critical apparatus, there have been established approaches and tools for many years. However, they mainly focus on subsentences or sentences. An efficient and easy-to-use automatic comparison of entire chapters or books still represents a research desideratum. The Locate, Explore, Retrace and Apprehend complex text variants (LERA) working environment presented here solves this issue. It is based on a two-stage collation approach: an efficient, fully automatic alignment of text segments, which can be paragraphs, subparagraphs or sentences, with interactive post-processing options, followed by the detailed comparison at segment level. Because aligning text segments, such as paragraphs, for more than two text witnesses is algorithmically challenging, we discuss the heuristics we developed in more detail. LERA combines the entire process of document management, tokenization/segmentation, normalization, alignment, and visualization with interactive control options and exploratory tools. It has already been and is being successfully applied in several Digital Humanities projects of different languages, e.g. for Arabic, French, Hebrew as well as German and English texts.
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