Abstract
A common problem for TEI software development is that projects develop their own custom software stack to address the semantic intricacies present in a deeply-encoded TEI corpus. This article describes the design of version 4 of the PhiloLogic corpus query engine, which is designed to handle heterogeneous TEI encoding through its redesigned abstract data model. We show that such an architecture has substantial benefits for software reuse, allowing for powerful TEI applications to be adapted to new corpora with a minimum of custom programming, and we discuss the more general and theoretical implications of abstraction as a TEI processing technique.
Highlights
By providing an endto-end TEI processing library, we allow developers to use the same abstract data model at all stages in the application and permit formatting software to work on a wide variety of TEI constructs and schemata
This enables developers to leverage their knowledge of their own corpora and the TEI Guidelines rather than delving into the minutiae of web frameworks and relational databases
We currently don't include any such modules in the standard PhiloLogic distribution, we are greatly encouraged by the emergence of complementary standards such as the W3C Open Annotation Data Model (W3C 2013), ISO MAF (ISO 2012), and LMF (ISO 2008), among others, and look forward to providing comprehensive support for annotation features in a future release
Summary
1. Document: jointly describes the contents of the TEI Header and the element itself. 2. Div-like: includes the component and division model classes, or other large container units. 3. Paragraph/Chunk: typically includes , , or similar elements. 4. Sentence/Phrase: by default, sentence objects are generated by the tokenizer. 6. Parallel objects: spans of text between milestone elements forming a "parallel hierarchy" of pages, lines, or other components
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