@still_reading@CamelNlp Also, note that you are taking the first analysis (not in any order), and not considering context. CT gives you the option of optimizing the selection of the appropriate analysis in context. See https://t.co/9n0UfoZzJn and https://t.co/mD82vYfLhH.
@still_reading@CamelNlp The CAMeL Tools (CT) analyzer does more than Tashaphyne (TSP) and requires more time to load resources.
If you time both TSP and CT after initializing the analyzer/stemmer you'll find CT is much faster.
On my machine CT took 0.0009 seconds vs 0.0019 with TSP. See code below:
🚨Shared Task Announcement🚨
Are you interested in language generation and in building user-aware NLP models targeting gender-marking morphologically rich languages?
We are happy to announce the Gender Rewriting Shared Task at @WANLP_Ar in @emnlpmeeting
https://t.co/QT7CN7xsCV
We are pleased to announce the first official release of CAMeL Tools, an open-source Python Arabic NLP toolkit for pre-processing, morphological modeling, dialect identification, named entity recognition, and sentiment analysis.
https://t.co/5VWigE9tvB
@UnfoldGames I'm based in the United Arab Emirates. While there is an https://t.co/6eEDul9zGY for local physical goods (this used to be a separate company that got acquired by Amazon), I have to go to https://t.co/MZj2gL0ZXr for all my ebooks. I tried .co.uk as well without luck.
"Unsupervised Acquisition of Inflectional Morphology" was accepted at #acl2020.
w/ Alexander Erdmann, Micha Elsner, Shijie Wu (@EzraWu), Ryan Cotterell (@ryandcotterell) and Nizar Habash (@nyhabash)
We're happy to share that our paper "Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging" (Nasser Zalmout and Nizar Habash) was accepted at #acl2020.