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The main purpose of this tool is to help users in extracting syntagmatic relations between words, lemmas and roots available in the Quran; these relations include identifying significant collocates and words’ co-occurrences. In addition, the tool also provides other helpful functionalities that complement the primary purpose, which include a Key Word In Context (KWIC) concordance, in addition to frequency lists of all words, lemmas and roots in the holy Quran. The main intended users of this...

The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words....

Hebrew Deflector tries to guess the root, the pattern and the form of a modern Hebrew word provided by the user. It uses the existing rules of the language to do that, and displays the list of possible answers. It is not a dictionary and it doesn't know whether the word (and the listed forms of it) exists or not. It also doesn't know anything about exception to the rules.

The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words....

Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy.