Structuring Arabic lexical and morphological resources using TEI: theory and practice

An Arabic word can be described according to its lexical and morphological information. The lexical information, conveyed by the root, consists of both semantic meaning and syntactic properties (e.g. parts of speech). The morphological information, encoded by patterns, is useful to group the words having similar syntactic, inflectional and semantic behaviour.Lexical analysis and morphological analysis have been separately described since the very first studies of the Arabic language. Although several scholarly works have illustrated Arabic lexicon models that encode semantic meanings, a systematic description of word patterns is still strongly lacking. In this work, we have implemented an exhaustive resource consisting of two levels: lexical and morphological. The lexical level collects information extracted from the dictionary al=q¯am¯us al=muh. ¯?t.. The morphological level describes pattern formalization, which allows to enrich word descriptions with additional semantic, morphosyntactic and inflectional information.To build our digital resource, taking into account primary source, lexical requirements, and reusability, we followed the guidelines provided by the Text Encoding Initiative (abbreviated as TEI). In particular, we adopted the TEI module for the encoding of digital dictionaries and lexicons to formally represent the medieval al=q¯am¯us al=muh. ¯?t. dictionary. Given the complexityof describing the morphological information present in the patterns, we also used the TEI module devoted to encoding feature structures.Consequently, we are building an exhaustive resource formed by the lexical and the morphological blocks. These two components are distinct but complementary resources where the lexical data are connected to morphological information. In addition, the morphological resource can be used as a stand-alone tool that allows the morphological analyzers to capture aspects of meaning that cannot be identified by current systems.