Constructing and Using Broad-coverage Lexical Resource for Enhancing Morphological Analysis of Arabic
Year: 2010
Type: conference-paper
Abstract: Broad-coverage language resources which provide prior linguistic knowledge must improve the accuracy and the performance of NLP applications.We are constructing a broad-coverage lexical resource to improve the accuracy of morphological analyzers and part-of-speech taggers of Arabic text.Over the past 1200 years, many different kinds of Arabic language lexicons were constructed; these lexicons are different in ordering, size and aim or goal of construction.We collected 23 machine-readable lexicons, which are freely available on the web.We combined lexical resources into one large broad-coverage lexical resource by extracting information from disparate formats and merging traditional Arabic lexicons.To evaluate the broad-coverage lexical resource we computed coverage over the Qur'an, the Corpus of Contemporary Arabic, and a sample from the Arabic Web Corpus, using two methods.Counting exact word matches between test corpora and lexicon scored about 65-68%; Arabic has a rich morphology with many combinations of roots, affixes and clitics, so about a third of words in the corpora did not have an exact match in the lexicon.The second approach is to compute coverage in terms of use in a lemmatizer program, which strips clitics to look for a match for the underlying lexeme; this scored about 82-85%.
Authors: Majdi Sawalha, Eric Atwell
Institution: University of Leeds
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2096183558