The aim with the present series, The Quran: Key Word Distribution, Correlations and Collocation Frequencies, is to present key data related to the lexicon of the Quran, in terms of Key Word distribution and lexical associations. The digital text used for this purpose is the Uthmani text of the Tanzil Quran Text. This text is widely used. All vocalized Arabic text is quoted unaltered in any shape or form from the Tanzil text. Unvocalized Arabic text and transcriptions are my own. In this series, each Key Word, here adjectives, nouns, proper nouns and verbs, is presented together with the following key data: Degree of Concentration, Weighted Distribution, Correlations and Collocation Frequencies. The Key Words are always referenced by their lemma and are sorted alphabetically according to Arabic and UNICODE order. In lemmatizing the words, no attention has been given to the semantics of each word. Only on rare occasion have similar forms of words or proper nouns been separated in order to avoid confusion. In assigning each word a lemma, Classical dictionaries and Quran commentaries, as well as modern Quran dictionaries have been consulted. Deciding on these is not always obvious, since classical dictionaries and commentaries sometimes either disagree or present divergent variant readings or root and lemma attributions. It is our hope and aim that this series contributes to Computational Linguistics and Digital Humanities in general, and Computational Linguistics research on the Quran in particular.

The aim with the present series, The Quran: Key Word Distribution, Correlations and Collocation Frequencies, is to present key data related to the lexicon of the Quran, in terms of Key Word distribution and lexical associations. The digital text used for this purpose is the Uthmani text of the Tanzil Quran Text. This text is widely used. All vocalized Arabic text is quoted unaltered in any shape or form from the Tanzil text. Unvocalized Arabic text and transcriptions are my own. In this series, each Key Word, here adjectives, nouns, proper nouns and verbs, is presented together with the following key data: Degree of Concentration, Weighted Distribution, Correlations and Collocation Frequencies. The Key Words are always referenced by their lemma and are sorted alphabetically according to Arabic and UNICODE order. In lemmatizing the words, no attention has been given to the semantics of each word. Only on rare occasion have similar forms of words or proper nouns been separated in order to avoid confusion. In assigning each word a lemma, Classical dictionaries and Quran commentaries, as well as modern Quran dictionaries have been consulted. Deciding on these is not always obvious, since classical dictionaries and commentaries sometimes either disagree or present divergent variant readings or root and lemma attributions. It is our hope and aim that this series contributes to Computational Linguistics and Digital Humanities in general, and Computational Linguistics research on the Quran in particular.

The aim with the present series, The Quran: Key Word Distribution, Correlations and Collocation Frequencies, is to present key data related to the lexicon of the Quran, in terms of Key Word distribution and lexical associations. The digital text used for this purpose is the Uthmani text of the Tanzil Quran Text. This text is widely used. All vocalized Arabic text is quoted unaltered in any shape or form from the Tanzil text. Unvocalized Arabic text and transcriptions are my own. In this series, each Key Word, here adjectives, nouns, proper nouns and verbs, is presented together with the following key data: Degree of Concentration, Weighted Distribution, Correlations and Collocation Frequencies. The Key Words are always referenced by their lemma and are sorted alphabetically according to Arabic and UNICODE order. In lemmatizing the words, no attention has been given to the semantics of each word. Only on rare occasion have similar forms of words or proper nouns been separated in order to avoid confusion. In assigning each word a lemma, Classical dictionaries and Quran commentaries, as well as modern Quran dictionaries have been consulted. Deciding on these is not always obvious, since classical dictionaries and commentaries sometimes either disagree or present divergent variant readings or root and lemma attributions. It is our hope and aim that this series contributes to Computational Linguistics and Digital Humanities in general, and Computational Linguistics research on the Quran in particular.

Does Job convincingly argue against a fixed system of just retribution by proclaiming the prosperity of the wicked—an assertion that distinctly runs contrary to traditional biblical and ancient Near Eastern wisdom? This study addresses this question, giving careful consideration to the rhetoric, imagery, and literary devices used to treat the issue of the fate of the wicked in Job’s first two rounds of dialogue, where the topic is predominantly disputed. The analysis will glean from related biblical and non-biblical texts in order to expose how Job deals with this fascinating subject and reveal the grandeur of the composition.

Jacob of Sarug's homily on Aaron the Priest, focusing on the period leading up to and including the death of Aaron described in Numbers 20:22–29.

Although the verse homilies of Jacob of Serugh are well known to lovers of Syriac literature, his stanzaic poetry, in the form of madroshe and sughyotho, have been largely forgotten. This volume contains twenty-five poems preserved in their complete form and attributed to Jacob in old manuscripts of the sixth/seventh to ninth/tenth century preserved today in the British Library, but largely originating from Deir al-Surian in Egypt.