Displaying 1 to 9 from 9 results

pynlpl - PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing

  •    Python

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotatation). The library is a divided into several packages and modules. It works on Python 2.7, as well as Python 3.

flat - FoLiA Linguistic Annotation Tool -- Flat is a web-based linguistic annotation environment based around the FoLiA format (http://proycon

  •    Javascript

FLAT is a web-based linguistic annotation environment based around the FoLiA format (http://proycon.github.io/folia), a rich XML-based format for linguistic annotation. FLAT allows users to view annotated FoLiA documents and enrich these documents with new annotations, a wide variety of linguistic annotation types is supported through the FoLiA paradigm. It is a document-centric tool that fully preserves and visualises document structure. FLAT is written in Python using the Django framework. The user interface is written using javascript with jquery. The FoLiA Document Server (https://github.com/proycon/foliadocserve) , the back-end of the system, is written in Python with CherryPy and is used as a RESTful webservice.

folia - FoLiA: Format for Linguistic Annotation - FoLiA is a rich XML-based annotation format for the representation of language resources (including corpora) with linguistic annotations

  •    Python

FoLiA is an XML-based annotation format, suitable for the representation of linguistically annotated language resources. FoLiA’s intended use is as a format for storing and/or exchanging language resources, including corpora. Our aim is to introduce a single rich format that can accommodate a wide variety of linguistic annotation types through a single generalised paradigm. We do not commit to any label set, language or linguistic theory. This is always left to the developer of the language resource, and provides maximum flexibility. XML is an inherently hierarchic format. FoLiA does justice to this by maximally utilising a hierarchic, inline, setup. We inherit from the D-Coi format, which posits to be loosely based on a minimal subset of TEI. Because of the introduction of a new and much broader paradigm, FoLiA is not backwards-compatible with D-Coi, i.e. validators for D-Coi will not accept FoLiA XML. It is however easy to convert FoLiA to less complex or verbose formats such as the D-Coi format, or plain-text. Converters are provided.

LaMachine - LaMachine - A software distribution of our in-house as well as some 3rd party NLP software - Virtual Machine, Docker, or local compilation/installation script

  •    Shell

LaMachine is a software distribution of NLP software developed by the Language Machines research group and Centre for Language and Speech Technology (Radboud University Nijmegen), as well as TiCC (Tilburg University). LaMachine is suitable for both end-users and developers. It has to be noted, however, that running the latest development versions always comes with the risk of decreased stability due to undiscovered bugs.

python-ucto - This is a Python binding to the tokenizer Ucto

  •    Python

This is a Python binding to the tokeniser Ucto. Tokenisation is one of the first step in almost any Natural Language Processing task, yet it is not always as trivial a task as it appears to be. This binding makes the power of the ucto tokeniser available to Python. Ucto itself is a regular-expression based, extensible, and advanced tokeniser written in C++ (https://languagemachines.github.io/ucto). Advanced note: If the ucto libraries and includes are installed in a non-standard location, you can set environment variables INCLUDE_DIRS and LIBRARY_DIRS to point to them prior to invocation of setup.py install.

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.

libfolia - FoLiA library for C++

  •    C++

This is a C++ Library, developed by Ko van der Sloot, for working with the Format for Linguistic Annotation (FoLiA). The software is intended for C++ developers, and provides a high-level API to read, manipulate, and create FoLiA documents. This software is a necessary dependency for various other tools that use FoLiA. libfolia is distributed under the GNU Public Licence v3 (see the file COPYING).

PICCL - A set of workflows for corpus building through OCR, post-correction, modernization of historic language and Natural Language Processing

  •    Groovy

PICCL offers a workflow for corpus building and builds on a variety of tools. The primary component of PICCL is TICCL; a Text-induced Corpus Clean-up system, which performs spelling correction and OCR post-correction (normalisation of spelling variants etc). PICCL and TICCL constitute original research by Martin Reynaert (Tilburg University & Radboud University Nijmegen), and is currently developed in the scope of the CLARIAH project.

ucto - Unicode tokeniser

  •    C++

Ucto tokenizes text files: it separates words from punctuation, and splits sentences. This is one of the first tasks for almost any Natural Language Processing application. Ucto offers several other basic preprocessing steps such as changing case that you can all use to make your text suited for further processing such as indexing, part-of-speech tagging, or machine translation. Ucto comes with tokenisation rules for several languages (packaged separately) and can be easily extended to suit other languages. It has been incorporated for tokenizing Dutch text in Frog (https://languagemachines.github.io/frog), our Dutch morpho-syntactic processor.