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RIDGES Herbology: designing a diachronic multi-layer corpus

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Abstract

This paper introduces a multi-layer corpus architecture with multiple tokenizations using the open source historical, diachronic corpus of German called Register in Diachronic German Science. The corpus contains herbal texts printed between the fifteenth and nineteenth centuries and is concerned with the development of a German scientific register, independent of Latin. We will discuss difficulties of transcribing, normalizing and annotating historical texts and will thereby argue for the advantages of multiple layers and multiple tokenizations. A virtually infinite number of annotations can be added to the corpus, without the need for deciding between or discarding interpretations. Thus, this flexible architecture enables multiple normalizations and types of annotation and is open to a wide range of research questions in the humanities. We provide case studies concerning the exploitation of our different normalizations as well as structural, register-specific and linguistic annotations. The corpus architecture allows for its reuse as a resource for corpus-based research approaches.

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Notes

  1. http://korpling.german.hu-berlin.de/ridges/index_en.html. The corpus is freely available under a CC-BY license at the LAUDATIO Repository http://hdl.handle.net/11022/0000-0000-2D85-8. Accessed 1 March 2016.

  2. The corpus texts were collected and initially prepared in several graduate and undergraduate seminars at Humboldt-Universität zu Berlin. The texts were extensively corrected and checked for consistency before publication. The corpus is growing; Version 5 (containing 36 excerpts, 183.724 tokens) was published in June 2016.

  3. The size of the text excerpts is chosen depending on the teaching context, i.e. whether the data is collected in a graduate or undergraduate seminar.

  4. Bayerische Staatsbibliothek https://www.bsb-muenchen.de/, Münchener Digitalisierungszentrum http://www.digitale-sammlungen.de/, Universitätsbibliothek Heidelberg http://www.ub.uni-heidelberg.de/helios/digi/digilit.html. Accessed 1 March 2016. The corpus is currently based on printed texts only. We used the original version wherever possible (that is, wherever we were able to find a high-quality scan) and the earliest available version otherwise. The complete bibliographical information for each text is given in the metadata. We plan to add some manuscripts at a later stage, and also envision adding some of the Latin sources.

  5. https://books.google.de/. Accessed 1 March 2016.

  6. http://corpus-tools.org/pepper. Accessed 8 June 2016.

  7. ANNIS, which stands for ANNotation of Information Structure, was originally designed to provide access to the data of the SFB 632—Information Structure, see http://corpus-tools.org/annis/. Accessed 1 March 2016.

  8. LAUDATIO, which stands for Long-term Access and Usage of Deeply Annotated Information, is an open access repository for historical corpora. http://www.laudatio-repository.org. Accessed 1 March 2016.

  9. There is an ongoing discussion in corpus linguistics on what constitutes primary data (cf. Claridge 2008; Himmelmann 2012, the discussion involves the roles of originals, pictures (scans), transcriptions, and normalizations). Here, we focus on the technical features of a corpus and do not want to engage in this discussion. We will briefly come back to the different notions of ‘text' in Sect. 3.5.

  10. In Sects. 3.1 and 3.2 we will discuss the tokenization and normalization for historical German.

  11. http://corpus-tools.org/salt/ Accessed 8 June 2016.

  12. Bird and Liberman (2001) proposed to use character offsets as a substitute for time-stamps in written texts, but since different tokenizations can have different base texts (unlike Fig. 1, where the exact same character sequence is tokenized in different ways) this is not applicable to our model. But even without time-stamps, the structure of a timeline allows us to model the alignment between different tokenizations. In contrast to Salt, the PAULA and ANNIS data models do not have the explicit concept of a timeline and thus need a different way to encode it. The solution to this problem is an automatic creation of a single artificial minimal tokenization (cf. Krause et al. 2012), where each artificial token corresponds to a timeline item. The conceptual tokenizations are represented as annotations on top of these artificial tokens and are flagged as segmentation layers. Technically, a segmentation layer is just a normal annotation layer, but flagging it as a segmentation layer makes it behave like one of a set of alternative tokenization layers that the search engine, ANNIS, treats as the basic text of a document. This affects both the initial view of search results and the ability to define search context and distance between search elements.

  13. Other corpus projects using a similar corpus architecture are Falko (Reznicek et al. 2013), PCC (Stede and Neumann 2014), Referenzkorpus Altdeutsch (Donhauser 2015), or Coptic Scriptorium (Zeldes and Schroeder 2015).

  14. For the corpus documentation see http://hdl.handle.net/11022/0000-0000-8253-F. Accessed 16 March 2016.

  15. http://korpling.german.hu-berlin.de/ridges. Accessed 16 March 2016.

  16. For the official Unicode table see www.unicode.org. Accessed 1 March 2016. An anonymous reviewer has asked why we have opted to use precomposed characters when possible and not to use combining diacritics. In principle, the TEI standard has taken an agnostic stance in this matter. Precomposed characters circumvent possible problems with regular expression engines that only have level 1 support for Unicode (e.g. when searching for a single grapheme cluster as described in http://unicode.org/reports/tr18/#Grapheme_Cluster_Mode). Not all glyphs have precomposed characters in Unicode and we use combining characters in this case.

  17. This is generally true even for incunabula which may contain rare glyphs. The Medieval Unicode Fonts Initiative (MUFI, http://folk.uib.no/hnooh/mufi/) is concerned with adding special characters represented in older texts to the Unicode standard. Accessed 1 March 2016.

  18. TEI stands for Text Encoding Initiative, for an introduction see Romary (2009) and Sect. 3.3. http://www.tei-c.org. Accessed 10 May 2016.

  19. See Voigt (2013) for guidelines, http://korpling.german.hu-berlin.de/ridges/download/v4/cleanV2README.txt. Accessed 1 March 2016.

  20. Note that there is a different way of dealing with the search problem, namely the mapping of different forms in the search itself, also known as fuzzy search. For further references on automatic normalization see Sect. 3.5.

  21. Duden (Dudenredaktion 2016) is the standard orthographic lexicon for German. Many other historical corpora follow modern reference lexicons in their normalization, cf. e.g. Rissanen (2012) and Donhauser (2015).

  22. Another problem of this approach is a conceptual one: Is it useful to map forms of one language to forms (and ultimately categories) of another language? Which interesting distinctions and properties are lost? This issue (similar to the debate about the comparative fallacy in second language acquisition research, see Bley-Vroman 1983) is interesting and needs to be discussed further.

  23. The text also contains the form das in both interpretations. The choice between das and dz seems to be driven by typographic needs. It seems that the correct alignment within the print space plays an important role for the early printers and that (at least sometimes) the choice of the shorter/longer form is driven by the need for less/more space rather than by linguistic considerations.

  24. There is also considerable work within the framework of the TEI relating to normalization and tokenization, as well as suggestions for multi-layer standoff approaches within the standard (see Heiden 2010; Pose et al. 2014).

  25. There are, among many others, Deutsches Textarchiv http://www.deutschestextarchiv.de/ (Geyken et al. 2012), the Duisburg-Leipzig Korpus romanischer Zeitungssprachen http://home.uni-leipzig.de/burr/CorpusLing/Korpusanalyse/default.htm (Burr et al. 2015), and Coptic Scriptorium http://copticscriptorium.org/, see Zeldes and Schroeder (2015). Accessed 1 March 2016.

  26. http://www.helsinki.fi/varieng/CoRD/corpora/HelsinkiCorpus/. Accessed 1 March 2016.

  27. Petrova, Svetlana; Donhauser, Karin; Odebrecht, Carolin; T-Codex (Version 2.1), Humboldt-Universität zu Berlin. https://korpling.german.hu-berlin.de/~annis/T-CODEX/corpus_description_tatian2.1.pdf, http://hdl.handle.net/11022/0000-0000-850C-D. Accessed 21 March 2016.

  28. Bennett, Paul; Durrell, Martin; Ensslin, Astrid; Scheible, Silke; Whitt, Richard; GerManC (Version 1.0), University of Manchester. http://www.llc.manchester.ac.uk/research/projects/germanc/. http://hdl.handle.net/11022/0000-0000-2D1B-1. Accessed 21 March 2016.

  29. Fürstinnenkorrespondenzkorpus. Lühr, Rosemarie; Faßhauer, Vera; Prutscher, Daniela; Seidel, Henry; Fuerstinnenkorrespondenz (Version 1.1), Universität Jena, DFG. http://www.indogermanistik.uni-jena.de/Web/Projekte/Fuerstinnenkorr.htm. http://hdl.handle.net/11022/0000-0000-82A0-7. Accessed 21 March 2016.

  30. Donhauser, Karin; Gippert, Jost; Lühr, Rosemarie; ddd-ad (Version 0.1), Humboldt-Universität zu Berlin. https://referenzkorpusaltdeutsch.wordpress.com/. http://hdl.handle.net/11022/0000-0000-7FC2-7. Accessed 21 March 2016.

  31. The element <lang> http://www.tei-c.org/release/doc/tei-p5-doc/de/html/ref-lang.html and attribute xml:lang, and the element <hi> which can be attributed information about the font http://www.tei-c.org/release/doc/tei-p5-doc/de/html/ref-hi.html. Accessed 1 March 2016.

  32. Due to the ongoing history of the corpus and the evolving annotation guidelines, not all texts contain annotation for German. If a document does not have an explicit annotation deu, we counted each dipl token without any annotation in the lang layer as German in the post hoc analysis.

  33. http://www.loc.gov/standards/iso639-2/php/code_list.php. Accessed 1 March 2016.

  34. Many of the texts contain Latin passages, ranging from words [often translations of the name of a herb or an illness, as in Example (1b)] to phrases and, sometimes, whole paragraphs. The texts also contain information (also often translations of the names) in other languages, such as Greek, French, or English.

  35. Currently it is the ‘Rat für deutsche Rechtschreibung’ http://www.rechtschreibrat.com/. Accessed 1 March 2016.

  36. http://sfs.uni-tuebingen.de/langbank/de/index.html Accessed 16 March 2016.

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Acknowledgements

We would like to thank Vivian Voigt and Laura Perlitz, our two very capable student assistants, who helped with many aspects of corpus creation and consistency checking. We would also like to thank the many students who took part in the digitization and basic annotation, as well as Uwe Springmann, Florian Zipser and three anonymous reviewers for comments that greatly improved the manuscript. The project has been generously funded by two Google Digital Humanities Research Awards.

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  1. Institut für deutsche Sprache und Linguistik, Humboldt-Universität zu Berlin, Dorotheenstraße 24, 10117, Berlin, Germany

    Carolin Odebrecht, Malte Belz, Anke Lüdeling & Thomas Krause

  2. Department of Linguistics, Georgetown University, Poulton Hall, 1421 37th St. NW, Washington, DC, 20057, USA

    Amir Zeldes

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Correspondence to Carolin Odebrecht.

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Odebrecht, C., Belz, M., Zeldes, A. et al. RIDGES Herbology: designing a diachronic multi-layer corpus. Lang Resources & Evaluation 51, 695–725 (2017). https://doi.org/10.1007/s10579-016-9374-3

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