Displaying 1 to 7 from 7 results

lemma - A Morphological Parser (Analyser) / Lemmatizer written in Elixir.

  •    Elixir

A Morphological Parser (Analyser) / Lemmatizer written in Elixir. It is implemented using a textbook classic method relying in an abstraction called Finite State Transducer. Documentation can be found at https://hexdocs.pm/lemma.

rnnmorph - Морфологический анализатор на основе нейронных сетей и pymorphy2

  •    Python

Morphological analyzer (POS tagger) for Russian and English languages based on neural networks and dictionary-lookup systems (pymorphy2, nltk). Скорость: от 200 до 600 слов в секунду на CPU, на GPU в несколько раз быстрее.

frog - Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch

  •    C++

Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch. All NLP modules are based on Timbl, the Tilburg memory-based learning software package. Most modules were created in the 1990s at the ILK Research Group (Tilburg University, the Netherlands) and the CLiPS Research Centre (University of Antwerp, Belgium). Over the years they have been integrated into a single text processing tool, which is currently maintained and developed by the Language Machines Research Group and the Centre for Language and Speech Technology at Radboud University Nijmegen. A dependency parser, a base phrase chunker, and a named-entity recognizer module were added more recently. Where possible, Frog makes use of multi-processor support to run subtasks in parallel. Various (re)programming rounds have been made possible through funding by NWO, the Netherlands Organisation for Scientific Research, particularly under the CGN project, the IMIX programme, the Implicit Linguistics project, the CLARIN-NL programme and the CLARIAH programme.

ITU-Turkish-NLP-Pipeline-Caller - A Python3 wrapper tool to help using ITU Turkish NLP Pipeline API

  •    Python

As I no longer have time to maintain this project I am looking for collaborators to help to maintain. You can sign up by sending a pull request which fixes a bug or adds a feature. For details of the pipeline, please check the pipeline page and the sources below.

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