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"XML-Print" is a joint project of the FH Worms (Prof. Marc W. Küster) and the University of Trier (Prof. Claudine Moulin) with support from TU Darmstadt (Prof. Andrea Rapp). Its goal is the creation of a XML formatter designated especially for the needs of the “Digital Humanties”. The project is funded by the DFG. Please visit https://sites.google.com/a/budabe.eu/xmlprint_de/kontakt and let us know, what you think about XML-Print – Does it meet your expectations?

...Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. Developed by The Natural Language Processing Group at Stanford University, a team of faculty, postdocs, programmers and students who work together on algorithms that allow computers to process and understand human languages. Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, automatic question answering, machine translation, syntactic parsing and tagging, sentiment analysis.

CLEiM (Cross Lingual Education in Medicine) is an opensource version of an Intelligent System which extract concepts from medical texts and provides qualified information. It integrates information from various sources. This system has been developed by the Intelligent System Group GSI (http://www.esi.uem.es/gsi/) at UEM University. We do NER (Named Entity Recognition) based on GATE platform. The installation is simple, you can use it as a Web application. It has been tested under apache-tomcat. The original system has been successfully used to carry out active learning activities with medical students. However, it could be interesting in much more knowledge fields.

The semantic annotation system OPTIMA is the result of Andreas Vlachidis PhD work, (supervised by Prof. Douglas Tudhope, University of Glamorgan, UK). OPTIMA performs the NLP tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word Sense Disambiguation using hand-crafted rules and SKOS terminological resources (English Heritage Thesauri and Glossaries). The resulted semantic annotations are associated with classes of the (ISO 21127:2006) CIDOC Conceptual Reference Model (CRM) and its archaeological extension, CRM-EH. ...

This project extends the ASV Toolbox from the Wortschatz-project at the University of Leipzig. It annotates terms extracted by the "TE" (Terminolgy Extraction) and "Namerec" modules with semantic resources.

An implementation of the Simplified Lesk algorithm for Germanet from the University of Tübingen.