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arXiv 2011.10970cs.AI
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DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings

The University of British Columbia(不列颠哥伦比亚大学);American University of Beirut(贝鲁特美国大学);Concordia University(康考迪亚大学);Arab Academy for Science and Technology(阿拉伯科学与技术学院)

Muhammad Abdul-Mageed, Shady Elbassuoni, Jad Doughman, AbdelRahim Elmadany, El Moatez Billah Nagoudi, Yorgo Zoughby, Ahmad Shaher, Iskander Gaba, Ahmed Helal, Mohammed El-Razzaz

英文摘要:

Word embeddings are a core component of modern natural language processing systems, making the ability to thoroughly evaluate them a vital task. We describe DiaLex, a benchmark for intrinsic evaluation of dialectal Arabic word embedding. DiaLex covers five important Arabic dialects: Algerian, Egyptian, Lebanese, Syrian, and Tunisian. Across these dialects, DiaLex provides a testbank for six syntactic and semantic relations, namely male to female, singular to dual, singular to plural, antonym, comparative, and genitive to past tense. DiaLex thus consists of a collection of word pairs representing each of the six relations in each of the five dialects. To demonstrate the utility of DiaLex, we use it to evaluate a set of existing and new Arabic word embeddings that we developed. Our benchmark, evaluation code, and new word embedding models will be publicly available.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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