Question answering
The QALL-ME framework
The QALL-ME framework is a free Service Oriented Architecture (SOA) skeleton for mutlilingual QA systems. The public project deliverable The QALL-ME Architecture Design Issues and QA Framework (Neumann et al. 2007) describes the principles of the multilingual open-domain Question Answering framework as well as some future directions. More information about technical details, online demonstration, and download links can be find here.
Web-based Question answering system
An experimental web-based question answering system, that answers factoid and definition questions in several languages from Textsnippets returned by standard search engines, as described in (Figueroa and Neumann, 2006) and (Figueroa et al., 2009). Test the new research version from here.
Cross-lingual open domain question answering
Quantico is a cross-lingual open-domain question answering system that can receive German questions and extracts exact answers from German or English documents either fetched from a local document collection or from the Web, cf. (Neumann and Sacaleanu, 2006) and (Sacaleanu and Neumann, 2007).
Information extraction
German text processing
SMES is a is an information extraction core system for real world German text processing. It provides a set of basic powerful, robust, and efficient natural language components and generic linguistic knowledge sources which can easily be customized for processing different tasks in a flexible manner, cf. (Neumann et al., 1997), (Neumann et al., 2000). Get more information from here.
German Named entity recognition and chunk parsing
Parts of SMES have also been realized as a standalone system called STP that recognizes named entities, online noun compounds and syntactic chunks by applying a cascade of finite state machines very efficiently, cf. (Neumann and Piskorski, 2002). This version is implemented in C++ and runs on Windows, Linux and MacOs. Please, contact me if you want more information about this version of SMES.
Platform for Named Entity Recognition
NER-Hub is a platform for Named Entity processing. It uses a voting strategy to combine the results produced by several existing NER systems (OpenNLP, LingPipe and Stanford), aiming at reducing the amount of errors produced by them individually. The system's architecture is based on the framework of OSGi - a Java service platform and module system, which offers fexibility in terms of component management. The project can be run as and accessed via a web service and comes with a graphical web user interface. We are currently working on making this NER-Hub platform open source.
Other Named Entity Recognition Tools
Links to other Named Entity Recognizers, which have been developed by my students are here.
Multilingual Dependency Parsing
MDParser is a very fast data-driven multilingual dependency parser developed by my student Alexander Volokh. MDParser is an especially fast system and therefore it is particularly suitable for processing very large amounts of data. Currently, we are using it in our research systems for recognizing textual entailment (RTE); for more details see (Volokh and Neumann, 2011) and (Volokh et al., 2010). We are planning to make the MDParser an open source, so in the meanwhile check this site.
Morphology
Morphix
Morphix is a very fast and robust morphological component for German. Besides inflectional analysis, it analyses compounds and is also able to generate wordforms from a given stem entry and some further (optional) morpho-syntactic information. Download Morphix from here.