TEI by ExampleModule 7: Critical EditingRon Van den BrandenEdward VanhoutteMelissa TerrasAssociation for Literary and Linguistic Computing (ALLC)Centre for Data, Culture and Society, University of Edinburgh, UKCentre for Digital Humanities (CDH), University College London, UKCentre for Computing in the Humanities (CCH), King’s College London, UKCentre for Scholarly Editing and Document Studies (CTB) , Royal Academy of Dutch Language and Literature, BelgiumCentre for Scholarly Editing and Document Studies (CTB)Royal Academy of Dutch Language and LiteratureKoningstraat 189000 GentBelgiumctb@kantl.beEdward VanhoutteMelissa TerrasCentre for Scholarly Editing and Document Studies (CTB) , Royal Academy of Dutch Language and Literature, BelgiumCentre for Scholarly Editing and Document Studies (CTB) , Royal Academy of Dutch Language and Literature, BelgiumGentCentre for Scholarly Editing and Document Studies (CTB)Royal Academy of Dutch Language and LiteratureKoningstraat 189000 GentBelgium
Licensed under a Creative Commons Attribution ShareAlike 3.0 License
9 July 2010TEI By Example.Edward VanhoutteeditorRon Van den BrandeneditorMelissa Terraseditor
TEI By Example offers a series of freely available online tutorials walking individuals through the different stages in marking up a document in TEI (Text Encoding Initiative). Besides a general introduction to text encoding, step-by-step tutorial modules provide example-based introductions to eight different aspects of electronic text markup for the humanities. Each tutorial module is accompanied with a dedicated examples section, illustrating actual TEI encoding practise with real-life examples. The theory of the tutorial modules can be tested in interactive tests and exercises.
en-GBproofing correctionstechnical revisionadded distinction gi — gi scheme="..." — tagfinal spellcheckreleaseauthoring
Module 7: Critical Editing
When texts are considered random combinations of strings, this can entertain interesting predictions about the completion of the complete works of William Shakespeare by a(n army of) hypothetical monkey(s) randomly hitting the keys on a typewriter (see the infinite monkey theorem). Indeed, to a computer, the textual universe is a library of Babel, in which every possible text is as likely (or rather unlikely) to exist as any other text. From this perspective, perfect duplicates may perfectly co-exist with gazillions of close approximations and texts that have nothing in common at all. In an intellectual, human context, where characters are ordered along (arbitrary) rules, two sensible texts will most likely have nothing in common at all, rather than being related in any way. In fact, the chances of identical texts can almost be ruled out to either perfect mechanical photocopies, or blatant cases of plagiarism, and as such be considered uninteresting from an intellectual point of view. However, especially in the context of greatly valued literary, cultural, and/or historical works, the odd chance that such a text has a closely resembling counterpart becomes quite interesting. It may at least indicate some kind of relationship between both texts, even provide insight in its transmission through time, shed light on its history and conception, perhaps tell us something about the creative process of its author, or by extension provide insights in The Creative Process in the working of the human mind. These domains of knowledge inform different kinds of theories of textual criticism, each with their own research interests, principles and practises. What they all have in common, however, is an attempt to represent related texts found in different physical witnesses as different versions of the same abstract work.
As we have seen already, in order to make this world of meaning accessible to/via computers, text encoding with TEI provides a sensible approach. Moreover, besides the general provisions for text encoding, the TEI Guidelines define a range of specific elements and mechanisms to represent textual variation in a sensible way for further analysis. The TEI Guidelines devote a complete chapter, 12. Critical Apparatus, to the documentation of specific elements that are grouped into the textcrit module for the encoding of textual variation. In order to use the elements covered in this tutorial module, you are thus required to include the dedicated textcrit TEI module in your TEI schema.For directions on composing a TEI schema by selecting TEI modules and elements, see .
Similar to all other TEI modules, the elements and attributes defined in the TEI textcrit module can be used for the encoding of existing source materials (be they in print or digital form), or the encoding of electronic documents from scratch. However, the use of this module in the context of electronic critical editing, adds another perspective to this traditional authorial/editorial angle (see Vanhoutte and Van den Branden 2009). Electronic or digital critical editions can be created from scratch either by encoding different primary source materials straight as a critical edition, or by generating the edition from previously encoded electronic transcriptions of those materials as independent texts in their own right. Therefore, the tags defined in the TEI textcrit module can be used to:
an existing print editiona digital edition, e.g., by recording some or all of the known variations among different witnesses to the text in a critical apparatus of variantsa digital edition from encoded transcriptions of the documentary source material
In the examples in this TBE module, critical editing with TEI will be understood as the act of encoding material sources in a TEI representation that allows for the creation or generation of a digital edition in some form (using any output format in the digital medium, e.g., HTML pages, PDF, flash movies,...), rather than digitising an existing critical edition. In this sense, the authorial/editorial angle of this TBE module differs from that of the other modules (focusing on the digitisation of a material source text in a certain genre). However, the strategies discussed in this tutorial for representing textual variation can equally be applied to the digitisation of existing critical editions. Where there are differences, these will be pointed out explicitly.
For example, consider following texts:
Some of these images may look more or less familiar to you: they are facsimiles from the first page of chapter 2 of the printed TEI Guidelines throughout their different incarnations, from version P2 (1992) to the latest version, P5 (2009). As you can imagine, the technological evolutions of these 17 years have prompted considerable changes to this chapter that introduces the technological background of text encoding with TEI, ranging from rephrasing, addition or deletion of notes, changes in italicisation, restructuring of paragraphs, etc. One way of approaching this textual variation could consist of encoding these text versions as physically distinct TEI documents, in which corresponding text structures could be aligned by a common identification mechanism. For example, the first couple of paragraphs in these 4 text witnesses could be encoded in different TEI documents as follows:
This would allow for maximal representation of the distinct material sources, and leave the identification of the actual variation either to further processing or human inspection. A variant of this approach could integrate the transcriptions of the text in all material witnesses in a single TEI document, and make use of appropriate linking attributes to point out the alignment between the different text structures. In their naivety, such systems are both redundant and crude. While providing all text of all text witnesses, and aligning the corresponding text structures, they provide little insight in the places where the different witnesses actually differ.
In order to encode the actual textual variation between the different text versions in a meaningful way, the TEI Guidelines provide a specialised module of elements and attributes that allow you to encode textual variation at word level. This TBE tutorial will first discuss how to describe the different text witnesses represented in the critical edition; next deal with the encoding of textual variants between these witnesses in isolation; then treat different ways of integrating such records of variation within the encoding of the critical edition; and finally point out potential problems and pitfalls when creating a critical edition with TEI.
Describing Text Witnesses
When creating, generating or digitising a critical edition, it is of crucial importance to document the text witnesses whose transcriptions it contains. This can be done in a listWit (list of witnesses) element, which can be put either in the sourceDesc section of the TEI header (when creating or generating a critical edition), or somewhere in the text, usually in the front section (when digitising an existing critical edition). The listWit element should describe each text witness in its own witness element. This element can contain a prose description of the witness in plain text, possibly enriched with a specialised element for bibliographic description (bibl, biblStruct, or biblFull). The witness definitions should provide a unique identification code in the xml:id attribute. This code is used as a sigil in the critical edition, in order to connect the textual variants with the respective witnesses in which they occur (see ). For example, the witness list for our critical edition of the TEI Guidelines could look as follows:
Such bibliographic descriptions of course are easier for printed works than for manuscripts; for the latter type of witnesses, some kind of description inside listWit is advised, preferably with a pointer (using ptr or ref) to a full description of the manuscript inside msDescription.
For a full discussion of the msDescription element, see section 10.2 The Manuscript Description Element of the TEI Guidelines, and section 220.127.116.11 The Witness List for examples of describing manuscript witnesses in a digital edition.
In a critical edition, it may make sense to discern groups of witnesses that have many text variants in common in comparison to other witnesses and can often be conveniently summarised in one sigil. In the witness list, witnesses can be grouped by wrapping their witness descriptions in nesting listWit structures. The common sigil then can be provided as the value for an xml:id attribute of the group’s listWit element. The nested witness groups can be labelled with a head element. For example, in our sample text witnesses it may make sense to discern those versions of the TEI Guidelines dealing with SGML, and those dealing with XML. This could look as follows:
The different text witnesses included in a critical edition should be documented in a listWit element. Such a list may occur in the sourceDesc section of the TEI header (for digital editions created or generated from scratch), or in the text of the edition, usually in the front section (for digital editions digitised from an existing edition). Each text witness should be described in a witness element, containing either a prose description as plain text, possibly enriched with specific TEI elements for bibliographic description (bibl, biblStruct, biblFull). An xml:id attribute must be provided for each witness, which is used as the sigil for this witness in the edition. Witness groups can be distinguished in separate nested listWit elements.
Encoding Textual Variants
Basic Organisation of an Apparatus Entry
Traditionally, printed critical editions have developed efficient mechanisms to represent textual variants on as little physical space as possible in what is commonly called a critical apparatus. Many types of apparatus exist, depending on the editorial theory, but all tend to put the different readings found in the different text witnesses on a par with one version of the text, which is commonly called the base text. The TEI Guidelines offer an analogous mechanism for representing textual variants in a concise way. A piece of text with corresponding variants in the different text witnesses, is encoded in an app (apparatus entry) element, which holds all different readings. Each reading must be encoded in a rdg (reading) element, which can be associated to its respective text witness by means of the wit attribute. Its value should point to the definition of the text witness in a listWit element elsewhere in the edition (see ). For example, let’s have a closer look at the chapter title in our sample:
[witness p2]Chapter 2
A GENTLE INTRODUCTION TO SGML[witness p3]Chapter 2
A Gentle Introduction to SGML[witness p4]2 A Gentle Introduction to XML[witness p5]v
A Gentle Introduction to XML
In above example, all text that differs from the corresponding fragment in any other witness is highlighted in yellow. Only the word A is shared between all text witnesses. In a digital edition of our sample, these stretches of variant text could be encoded in two apparatus entries:
In this example, both textual variants are encoded as two apparatus entries, with four readings each. Each rdg element points to the definition of its corresponding text witness by means of the sigla in its wit attribute. Notice how each sigil starts with a # sign, because it addresses the xml:id value of a witness element in the edition.Notice, how the TEI Guidelines offer the means to encode textual variation, without imposing any theoretical assumptions on how to encode an apparatus for the variants in different texts. The treatment of variation in different text versions is an explicit theoretical act of interpretation, and it is up to the encoder to determine corresponding text fragments, and where to delimit stretches of variation. Likewise, the examples in this TBE tutorial module are fairly theory-neutral, in that they tend to use the maximal length of differing text fragments as guiding principle for the demarcation of textual variants.
In printed critical editions, the assumption of a base text against which all other versions are compared is quite common. Therefore, besides readings, a TEI apparatus entry can also contain a lem (lemma) element, identifying the reading it contains as a preferred reading, according to the editor’s theory of the text. Notice that if a lem element is used, it must occur as the first element inside app. If version p2 were considered the base text to the edition of this sample, the previous example could be encoded as follows:Because in the context of electronic critical editing a preferred reading in a lem element is fairly theory-dependent, the examples in this TBE tutorial module will mostly just list all variants as equal rdg elements. You have to know, however, that each app element may always specify one of its readings as lemma (lem) as well.
In order to make this representation more efficient, identical readings can be collapsed into one single rdg element, by combining the sigla into a list separated by white spaces in the wit attribute:
Remember how we distinguished different witness groups in the previous section of this tutorial? This allows us to rewrite the sigla of readings shared by the versions of the TEI Guidelines dealing with either SGML or XML, using the group identification code for the corresponding group of witnesses:
You should consider an app element as a cross-section of a text fragment over all of the different text witnesses. This means that all lem and rdg contents should be interpreted as mutually exclusive alternatives. Therefore, each text witness listed in the wit attributes inside an app element should occur only once. Ideally, this should be the minimal requirement as well, so that each apparatus entry contains one corresponding text fragment across all different text witnesses included in the edition (although this is not strictly necessary when the edition uses one base text: see ).
Each variant in a TEI encoded critical edition should be encoded as an apparatus entry, in an app element. An apparatus entry contains the different textual variants found in the text witnesses, encoded in different rdg (reading) elements. If the edition considers one of the text witnesses as the base text, the readings from that witness can be encoded as a lemma instead, in a lem element. Each lem or rdg element should indicate the text witness(es) it corresponds to in a wit attribute. The value of this attribute consists of a white space separated list of pointers to the xml:id code(s) of the witness element(s) describing the corresponding text witness(es).
In both variants considered so far, arguments could be made for (re)grouping the readings. In the first apparatus entry, reading p5 is set apart from all others because of the diverging chapter number. In the second apparatus entry, one possible case for explicit grouping could be the genetic similarity of the variants in those versions of the TEI Guidelines dealing with SGML or XML.
One way of grouping readings is provided by a rdgGrp element. It can be wrapped around rdg elements in an apparatus entry, in order to indicate their relatedness in some way. This rdgGrp really is nothing more than a wrapper, that can list the sigla of the text witnesses it groups in an own wit attribute. For example, the readings in the previous example could be grouped as follows:
When you take a closer look at these variants, you’ll see that some of these readings contain common text as well. In the first variant, the number 2 is shared between both teiSGML readings, and the p4 reading. In the last variant, the p2 and p3 readings are set apart by the common phrase SGML, as opposed to XML in the teiXML readings. Yet, both p2 and p3 text witnesses vary internally in their use of capitals. Such refinements can’t be expressed using the rdgGrp grouping mechanism, as a rdgGrp element can only contain rdg or lem elements. If this grouping is to be maintained, you could express them in a more fine-grained manner using another grouping mechanism: introducing nesting app elements in the rdg elements that share common text as well as variant readings:
In the first variant, the apparatus distinguishes between those readings whose heading refers to the second chapter (teiSGML and p4), and reading p5, which refers to chapter five. However, as the first group of readings shows internal variation, this can be expressed in further nesting app elements (see the nesting app elements for the Chapter sub-variant, and the line break). The common text can be encoded as plain text contents of the grouping rdg element (see the 2, which occurs in all readings of the group: teiSGML, and p4). In the second variant, the readings corresponding to the text witnesses dealing with SGML are set apart from those dealing with XML. Since the first group of readings contains internal variation, the variant text (Gentle Introduction to) is wrapped in a nesting app element, while the common text (SGML) appears as plain text inside the grouping rdg element.
When so desired, related readings can be grouped using one of two mechanisms. The first one wraps a dedicated rdgGrp element around related readings. This element can only contain lem and rdg elements. A more sophisticated way of grouping readings is provided by using nesting app structures inside a rdg element.
So far, the most elaborate encoding of the chapter’s title in the different text witnesses looks as follows:
Admittedly, this organisation is not the most intuitive one, mostly because it mixes different perspectives:
a content-oriented one in the first apparatus entry, grouping those variants with a common reading (i.e., the chapter number referred to)a genetic-oriented one in the second apparatus entry, grouping the readings according to the groups of witnesses (i.e., those occurring in the versions of the TEI Guidelines dealing with SGML or XML)
However, this is not necessarily the most interesting perspective, for it obscures some obvious correspondences. For example, there is no way of deducting the correspondence between the lb reading occurring in three of the four witnesses, as it is buried in two different reading groups. There is no reason, however, not to reorganise these apparatus entries in more atomic units:
One could argue that on closer examination, not all of these variants have the same status: some are more substantive than others. This may be pointed out at the level of the individual readings, by means of a type attribute. In this way, we could for example distinguish between orthographic readings (differing only in their spelling or presentation) and substantive readings (differing in meaning):
With this distinction in place, the type of reading could be adopted as guiding principle to derive larger stretches of variation: only when two subsequent variants only have orthographically different readings, they can be merged to one apparatus entry. Notice also, how in this case all readings for the different apparatus entries share the same type. This can be encoded at the higher level of the apparatus entry as well, simply by providing a type attribute for the app element:
The rdgGrp, too, can have a type attribute for specifying the nature of the group of readings it holds. For example, we could revisit the earlier grouping example using rdgGrp:
The readings inside rdg and lem can be categorised with a type attribute, in order to indicate what type of variant they contain. When readings are grouped using rdgGrp, the type attribute equally can indicate what type of variants the reading group consists of. When an apparatus entry only contains variants of the same type, this may be expressed by the type attribute at the app level.
Besides witness (wit) and type information (type), readings and lemmas can provide more information about the readings they hold, in dedicated attributes. One type of information that is particularly useful for critical editions of manuscript source materials, is the identification of a document hand that is responsible for a certain reading, especially when its text witness has been written by different hands. This can be expressed in a hand attribute, which points to the definition of that hand in the TEI header (see ). This could be applied to our example texts: although the TEI Guidelines are not manuscripts, they are written collaboratively by a team of editors who could be considered document hands. Suppose that we could determine who was responsible for what change in the different versions included in our example critical edition, this could be encoded as follows:
Of course this attribution is subject to a greater or lesser deal of interpretation (especially in this contrived example). Therefore, it makes sense to indicate who is responsible for this interpretation. This can be expressed in a resp attribute, which can point to an individual responsible for some aspects of the digital edition, as identified in the TEI header (see ). As always, the resp attribute applies to all aspects of the element it is attached to, and can equally be used to indicate the responsibility for an unsure transcription of a reading. As the hand attribution in the previous example can be considered quite putative, it makes sense to provide responsibility information as well:
Using attributes on rdg holds the danger of overgeneralisation, as in following example:
This example is incorrect because the first reading of the first apparatus entry overgeneralises the hand information for the p3 witness, and the last reading of the last entry incorrectly attributes the hand information for the p5 witness. It can be done, however, using a dedicated witDetail element, which is intended to provide more information about a specific reading in an apparatus entry. It must have a wit attribute, identifying the specific text witness it provides more information for. In order to anchor it to a specific rdg element, a target attribute can be used to point to the xml:id of the concerned rdg element. This implies that the reading concerned must be formally identified with an xml:id attribute. For example, the previous example could be corrected as:
The witDetail element is a specialised type of note, which means it can occur at many places in the document: either inline at the place of the reading needing further specification, or grouped together elsewhere in the document. The TEI Guidelines recommend to place this element inside app, immediately after the lem or rdg element it provides more information for.
Lemma (lem) and readings (rdg) can be further qualified by means of attributes. The resp attribute can be used to identify the person responsible for the encoding of the reading, while the document hand responsible for that particular reading can be referred to in a hand attribute. When more detailed information is to be given for a particular reading in a particular text witness, this can be done in a witDetail element, whose wit attribute must point to the concerned text witness, and whose target attribute can be used to point to the identification code of the affected reading(s).
Encoding Variation in Texts
After this discussion of the encoding of textual variation itself, it is time to have a look at the bigger picture: how do you integrate these variants into an electronic critical edition? The TEI Guidelines provide 3 different mechanisms for integrating apparatus entries in the encoding of texts (don’t let the names intimidate you):
apparatus entries are linked to the identified text blocks in a base text that contain the respective lemmas [I, E]apparatus entries are linked to explicitly identified start and end positions in a base text [I, E]apparatus entries are encoded inside a transcription of the common (invariant) text of all text witnesses [I]
In this overview, the [I] and [E] labels indicate where an apparatus encoded with that method can be physically located with regards to the transcription of the (base) text it is linked to:
the apparatus is located outside the transcription of a base text, either in some other part of the TEI document containing the transcription, or in a physically distinct document → location-referenced, double end-point attachmenteach apparatus entry is located inline in the transcription of a (base) text, at the place where the variant occurs → location-referenced, double end-point attachment, parallel segmentation
The method chosen and the physical location of the apparatus must be encoded in the TEI Header, in the variantEncoding element inside the encodingDesc section. This is an empty element with two mandatory attributes (see ):
method: indicates the method of linking the critical apparatus to the text: either location-referenced, double-end-point, or parallel-segmentation.location: indicates the location of the critical apparatus with regards to the text: either external or internal.
The TEI Guidelines offer 3 methods for linking the critical apparatus to the text. The method chosen must be documented in the encodingDesc section of the TEI header, in a special variantEncoding element. This is an empty element with 2 mandatory attributes. The method attribute specifies the method of linking the apparatus to the text (either location-referenced, double-end-point, or parallel-segmentation). The location attribute specifies the location of the apparatus relative to the text (either external or internal).
The Location-Referenced Method
The location-referenced method links an apparatus entry to a base text, by anchoring it to the text structure in the base text where the variant occurs. This can be done either internally (inside the running text), or externally (outside the running text).
In an internal location-referenced apparatus, the apparatus entries are encoded within the text structures in which the variants occur. The exact location, however, is unimportant. For example, the second paragraph could be encoded as follows:
Notice how the apparatus entries can occur anywhere as long as it is inside the text structure (in this case, the p element) that contains their variants. The same method can be used for an external apparatus, in which the textual variants are encoded either at a different place inside the base text, or in a physically distinct TEI document. In this external apparatus, each apparatus entry must have a specific attribute: loc. Its value should refer to the canonical reference of the text structure that contains the variants concerned. In an external apparatus, the previous example could look as follows:Notice, how the loc attribute does not refer to an xml:id value of the text structure concerned, but to its canonical reference. For more information, see the documentation of the app element, and section 2.3.5 The Reference System Declaration of the TEI Guidelines.
In these examples, the p5 version of the TEI Guidelines is adopted as the base text to which the apparatus entries are linked. This is the sole text witness for which a full transcription is provided in the electronic critical edition using this reference method. Because of this, the reading of this base text may be omitted from the app elements, as in the examples above. Due to the implicit nature of the location references of the apparatus entries, it may be hard to identify the exact places with textual variation. Therefore, the reading of the base text may equally be provided in the apparatus entries inside a lem element; combined with string matching, this can help the user of the edition to find out where the actual variation occurs (but notice the difficulty with apparatus entries encoding additions to the base text, as in the second app element of following example):
The location-referenced method uses an implicit anchoring technique to link the apparatus entries with the base text. In an internal apparatus, the apparatus entries can occur anywhere inside the text structure in which their variants occur. In an external apparatus, the link is established through the use of the loc attribute on the app elements, which points to a canonical reference of the relevant text structures in the base text.
The Double End-Point Attachment Method
The double end-point attachment method links an apparatus entry to a base text, by anchoring it to the exact start and end positions of its lemma in the base text. This can be done either internally (inside the running text), or externally (outside the running text).
In an internal double end-point attachment apparatus, the apparatus entries occur immediately after their lemma in the transcription of the base text. A specific from attribute must be used to point exactly at the starting point of the preceding lemma in the text. Its value should be a pointer to the formal identification code of an element in the base text that corresponds to the start of the lemma. If this point coincides with the start of an existing text structure, the identification code of its element may be used; otherwise, an empty anchor element must be inserted in the base text, whose sole purpose is to provide a formal code in its xml:id attribute. For example, an internal double end-point attachment apparatus for the example in the previous section could look as follows:
An external double end-point attachment apparatus is very similar to its internal equivalent, apart from the fact that the apparatus entries are located outside of the running text. Due to this physical separation, the need arises to explicitly point out the end point of the lemma in the base text as well (again, either using the xml:id attribute of an existing text structure, or that of an explicit anchor element). In order to refer to this end point of the textual variation, the app element must have another attribute: to, pointing at the identification code of the relevant point in the base text. For example, an external apparatus for the previous example could look as follows:
Of course, here too, the lemma of the base text can be explicitly recorded in the apparatus entries as well:
The double end-point attachment method provides a means to explicitly anchor an apparatus entry to the exact position where its lemma in the base text differs from one of the other readings. In an internal apparatus, the apparatus entries should be placed immediately after the base text’s lemma. Each app element must have a from attribute pointing to the xml:id identification code of an element indicating the start of the lemma in the base text. In an external apparatus, the apparatus entries must formally identify the end point of the lemma as well, using a to attribute that points to the xml:id identification code of an element indicating the end of the lemma in the base text. If no other elements are available, these xml:id attributes may be encoded on empty anchor elements inside the base text.
The Parallel Segmentation Method
Contrary to both other methods, the parallel segmentation method only allows for the encoding of an inline apparatus. Similarly to an internal double end-point attachment apparatus entry, a parallel segmented apparatus entry is encoded inline, at the exact place where the variation occurs. However, a parallel segmented apparatus entry encodes all readings as equal variants, thus interweaving the common (invariant) text of all text witnesses with apparatus entries that contain all different alternative readings. In this sense, the notions of a base text and lemma become obsolete: all text that is common, is shared; all varying text is encoded as a separate reading in an apparatus entry. Because of this exact anchoring at the place of occurrence in the palimpsest text, no specific attributes are necessary for the app element. For example, the preceding example can be expressed as a parallel segmented apparatus as follows:
The parallel segmentation method encodes all variants as equal readings inside apparatus entries that are located at their precise place of occurrence in all texts. This results in a single text that contains an integral view on both the common text and the textual variants. Because of this, the notions of base text and lemma become irrelevant.
Until the release of version 2.9.1 of the TEI Guidelines in 2015, lem and rdg could only contain phrase-level elements. For a very long time, this had caused problems for variants that involve larger structural units. Yet, since version 2.9.1, lem and rdg can contain chunk-level elements such as div, p, ab, lg, and l. This addition has greatly increased the use of lem and rdg for encoding real-life textual variation.
One tough problem remains, however, when textual variation occurs on a structural level. For example, if you look closely at the facsimiles of the TEI Guidelines above (see ), you’ll notice that there is a paragraph shift at the sentence starting with Historically, the word markup has been used :
in the p2 and p3 versions, this sentence starts the third paragraphin the p4 and p5 versions, this sentence is part of the second paragraph
This poses a harder encoding problem, as it involves markup itself (i.e., the end and start tag of the third paragraph are the subject of variation). As XML requires proper nesting of elements, this is a problem in any XML representation of this kind of structural variation. Again, two strategies could be followed (none of which is ideal, however):
Encode structural variants as variant structures. However, this may obscure their alignment.Encode structural variants using milestone elements instead of full-blown XML structures. However, depending on your view on the texts, this could be considered a less orthodox approach, as it implies some notion of a base text that determines the encoding of the others.
The first option would compare the individual transcriptions of these text witnesses, some of which spread more or less the same textual contents over 3 paragraphs, while others use only 2 paragraphs. In a parallel segmented apparatus, this might look as follows:
This approach treats the shifting paragraph as a variant in its own right, that is present in some witnesses (p2 and p3), while absent in the others (p4 and p5). The second apparatus entry then omits the text of p2 and p3, while including the (corresponding) text of p4 and p5. However, as this example illustrates, the alignment of the corresponding text fragments between both groups of witnesses (those starting a new paragraph and those that don’t) is lost: there is no way of telling how the phrases SGML is an international standard . More exactly, SGML (in p2 and p3) and XML is an extensible markup language . More exactly, XML correspond. This kind of encoding could be less problematic when generating an electronic critical edition (in which case the more complicated apparatus encoding could be generated by an automatic collation routine). When creating a digital edition, the construction of such a more complex apparatus entry could be less desirable.
The other solution would be to encode the paragraph break in the p2 and p3 versions using an empty milestone marker: an empty element that indicates some kind of structural boundary in the text where it occurs, as in this parallel segmented example:
Since the milestone paragraph boundary marker (milestone unit="p") removes the intrusive XML boundaries, this allows us to compare the text between all versions. However, this implies that the encoding of the third paragraph in the p2 and p3 versions is suppressed, in contrast to the other paragraphs in these text versions. This could be less a problem when creating an electronic critical edition, rather than when generating one. In the latter case, the milestone encoding would reflect a dependency on a base text (that does not have the paragraph break). Moreover, it presupposes some kind of structural alignment prior to the encoding of the individual texts.
Problems can arise when the variation involves text structures as well, giving rise to problems of overlapping XML structures. This can be avoided by either ignoring the possible alignment of such structures in the apparatus, or paraphrasing some structural boundaries with empty milestone elements.
This tutorial module has focused on the encoding of textual variation in different text witnesses. Although the determination of textual variation itself can depend on the editorial theories for the critical edition, and the TEI Guidelines offer many possibilities to encode textual variation, we’ll conclude with a possible encoding as a critical edition of the text samples we used in this tutorial module. In this example, we chose for a parallel segmented internal apparatus, which could look as follows:
You have reached the end of this tutorial module covering an introduction to critical editing with TEI. You can now either
proceed with other TEI by Example moduleshave a look at the examples section for the critical editing module.take an interactive test. This comes in the form of a set of multiple choice questions, each providing a number of possible answers. Throughout the quiz, your score is recorded and feedback is offered about right and wrong choices. Can you score 100%? Test it here!
Vanhoutte, Edward, and Ron Van den Branden. 2009. Describing, Transcribing, Encoding, and Editing Modern Correspondence Material: a Textbase Approach. Literary and Linguistic Computing24 (1): 77–98. 10.1093/llc/fqn035.