In “Linear to Table, Table to Linear” (KITAB Project Blog), Lorenz Nigst (Aga Khan University) uses the KITAB Project’s diff viewer to examine text reuse across two manuscripts “containing a short narrative involving Muḥammad Khawārazmshāh…[on] dream interpretation.”
In “Lemmatization as a Classification Task: Results from Arabic across Multiple Genres” (arXiv), Mostafa Saeed (New York University Abu Dhabi) and Nizar Habash (New York University Abu Dhabi) observe that “Lemmatization is crucial for NLP tasks in morphologically rich languages with ambiguous orthography like Arabic, but existing tools face challenges due to inconsistent standards and limited genre coverage.” Their paper “introduces two novel approaches that frame lemmatization as classification into a Lemma-POS-Gloss (LPG) tagset, leveraging machine translation and semantic clustering….[R]esults show that classification and clustering yield more robust, interpretable outputs, setting new benchmarks for Arabic lemmatization.”
