🤖 AI Summary
Existing Arabic–English dictionaries are predominantly available in unstructured textual formats, rendering them unsuitable for direct use in natural language processing tasks. This work addresses the absence of standardized microstructural organization in the widely used *Al-Mawrid* dictionary by proposing a semi-automatic structuring approach grounded in inductive rules, achieving the first hierarchical parsing of its lexical entries. The method employs Parsing Expression Grammars (PEG) to construct a core parser that explicitly models subentries, definition phrases, domain labels, cross-references, and translation equivalents. Experimental results demonstrate that the proposed pipeline effectively converts the dictionary into a machine-readable format, exhibiting both practical feasibility and reasonable accuracy in structuring non-standardized lexical resources.
📝 Abstract
Dictionaries are rich sources of lexical information about words that is required for many applications of natural language processing and human language technology. However, publishers prepare printed dictionaries for human usage not for machine processing. This paper presented a method to structure partly a machine-readable version of the Arabic-English Al-Mawrid dictionary. The method converted the entries of Al-Mawrid from a stream of words and punctuation marks into hierarchical structures. The hierarchical structure expresses the components of each dictionary entry in explicit format. A dictionary entry is composed of subentries and each subentry consists of defining phrases, domain labels, cross-references, and translation equivalences. We designed the proposed method as cascaded steps where parsing is the main step. We implemented the parser using the parsing expression grammars formalism. In conclusion, although Arabic dictionaries do not have microstructure standardization, this study demonstrated that it is possible to structure them automatically or semi-automatically with plausible accuracy after inducing their microstructure.