Open Source Library Management Software

Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data.

qtrans is an offline dictionary (word translator written in Qt5/KF5 or Qt5 only or Qt6/KF6). It uses Babylon (*.dic, *.bgl), StarDict (*.dict, *.dict.dz: *.ifo), Dictd and FreeDict (*.dict, *.dict.dz: *.index) as well as plain text (*.dic.txt) dictionaries. Plain text dictionaries should have the format: "expression [tab] definition". https://software.opensuse.org/package/qtrans https://software.opensuse.org//download.html?project=home%3Atkb&package=qtrans

The Key Store is a directory where users can find the symbolic meaning to a word as defined in Holy Scripture. These are often referred to as the keys of the Kingdom of Heaven. Much like a secret code, the directory exposes a universal dialect, all but nearly lost throughout the Dark Ages of time. Yet, fragments of this language remained until today such as, Father = Time and Mother = Nature. The database is expandable to grow as more entries and the sources are uncovered.

Before Unicode, there were several competing character encodings for the Coptic script. For instance, one group of fonts might map Coptic letters Γγ to Latin keys Gg, while another group might map them to Latin keys Jj. There are several reasons for the user to opt for legacy rather than Unicode encodings. Two deserve special mention. First, there are certain marks used in Biblical and other textual criticism that do not appear in Unicode; second, it is far easier to type in a legacy encoding and then turn it into Unicode than to type directly in Unicode. This package aims to act as a stepping stone to Unicode, by including several legacy fonts hard-coded to take advantage of the multiple encodings, as well as a UNIX shell script, in multiple shell languages, to transcode between these encodings. All twelve encodings in wide use are supported. The fonts in this package are compatible with many operating systems; the shell scripts support Mac and Linux (more soon).

we make a program that can find the poem meter name (called Bahar in Arabic) by Arud science, this science provides a methodology to classify Arabic poems into standard 16 meters, to help a user to find the meter name for any Arabic poem. And we discuss the solutions for problems, from the starting phase to the result, using regular expression and context free grammar (CFG). And the result 75% of the verse is found its meter, when input enters correctly. يقوم هذا البرنامج بايجاد البحر الشعري لاي بيت شعر يتم ادخاله بشكل صحيح بنسبة دقة (75% . وقد تم استخدام قواعد السياق الحر* للتوصل الى النتيجة . * context free grammar (CFG)

new ones can be found at https://code.google.com/p/ooc-gcc/

This is a Korean to English and English to Korean program utilizing Naver and Daum APIs. Additional languages will be supported in the future.

Itunes Library Parser can parse the Itunes library, read the Tracks & Playlists as Java objects and thereby perform all sorts of operations on the files such as read itunes stored data about the tracks and playlists. One of the coveted feature would be to transfer the playlists onto non-apple devices such as Android.

A C++ library to scan Homeric Greek (dactylic hexameter) and output the meter.

Open-Tamil is a full featured Tamil text processing library in Python. It works fully in Python 2, 3. Published via pip - python package index. See: https://pypi.python.org/pypi/Open-Tamil/0.67