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It consists of two subcorpora; one contains the English originals and the other their Arabic translations. As for the English subcorpus, it contains 3,794,677 word tokens, with 78,606 word types. The Arabic subcorpus has a slightly fewer word tokens (3,755,741), yet differs greatly in terms of the number of word types, which is 143,727.
It has Arabic to English translations and English to Arabic, as well as a significant quantity of technical terminology. It is useful to translators as its search results are given in context. [ 6 ] Almaany offers correspondent meanings for Arabic terms with semantically similar words and is widely used in Arabic language research. [ 7 ]
Though early accounts of Arabic word order variation argued for a flat, non-configurational grammatical structure, [24] [25] more recent work [23] has shown that there is evidence for a VP constituent in Arabic, that is, a closer relationship between verb and object than verb and subject. This suggests a hierarchical grammatical structure, not ...
Reverso has been active since 1998, with the aim of providing online translation and linguistic tools to corporate and mass markets. [3] [4] In 2013 it released Reverso Context, a bilingual dictionary tool based on big data and machine learning algorithms. [5] In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies.
Arabic is a Semitic language and English is an Indo-European language. The following words have been acquired either directly from Arabic or else indirectly by passing from Arabic into other languages and then into English. Most entered one or more of the Romance languages, before entering English.
In addition to the translation, a bilingual dictionary usually indicates the part of speech, gender, verb type, declension model and other grammatical clues to help a non-native speaker use the word. Other features sometimes present in bilingual dictionaries are lists of phrases, usage and style guides, verb tables, maps and grammar references.
Rule-based machine translation (RBMT; "Classical Approach" of MT) is machine translation systems based on linguistic information about source and target languages basically retrieved from (unilingual, bilingual or multilingual) dictionaries and grammars covering the main semantic, morphological, and syntactic regularities of each language respectively.
Similarly, when you look up the word for one in German, you won't find all 24 manifestations (4 cases x 2 numbers x 3 genders) of it, you'll find ein unless you're looking up the grammar, which would be more confusing than this instance since the declensions in German often change the entire form and spelling of the word whereas Arabic happens ...