Katja Markert's Research

My research interests centre on  computational linguistics. More specifically, I am interested in using  knowledge-based and  statistical techniques for the automatic treatment of problems in semantics, pragmatics and discourse. I am always interested in bright new PhD students with an NLP or good computer science/mathematical background. I

Recent research and ongoing research include :

• Automatic treatment of regular polysemy and metonymy. In the Mascara project, Malvina Nissim and I explored supervised and unsupervised machine learning techniques for metonymy recognition. We also produced an annotation scheme for metonymies and developed a freely available corpus annotated for metonymies, which is available from my Data page. Our approach for annotation and learning has been adapted for German at the University of Hagen as well as for French. The Business School at the University of Leeds has used our data to research the conceptualisation via metaphor and metonymy of organisations. We also organised a metonymy recognition competition in conjunction with SemEval 2007 in Prague.
• I am interested in opinion mining. Currently, my PhD student Fangzhong Su develops a system to recognise subjective and obnjective senses of words in WordNet. First results are being published in Coling 2008.
• The recognition of textual entailment and textual inference. Johan Bos and I participated in the Textual Entailment competitions organised in 2005 and 2006 and have developed a system for the automatic recognition of textual entailment that integrates deep and shallow semantic analysis within a machine learning framework. The part of the system performing deep semantic analysis can be downloaded on the Nutcracker website.
  
• Anaphora Resolution: In collaboration with Malvina Nissim and Natalia Modjeska,I used simple web queries for bridging the knowledge gap in the resolution in non-pronominal anaphora. We have integrated a web-based feature into a machine learning algorithm for other-anaphora and developed web-based algorithms for the resolution of definite NP coreference as well.
• Entity Recognition: I was involved in the SEER project at the University of Edinburgh and Stanford University, which has the generalization of current entity recognition tasks as its goal.
  

Please visit my publication page for papers describing my research results.

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