Learn More
This report describes the system developed by the University of Edinburgh and the University of Sydney for the TREC-2005 question answering evaluation exercise. The backbone of our question-answering platform is QED, a linguistically-principled QA system. We experimented with external sources of knowledge , such as Google and Wikipedia, to enhance the(More)
We present improvements and modifications of the QED open-domain question answering system developed for TREC-2003 to make it cross-lingual for participation in the Cross-Linguistic Evaluation Forum (CLEF) Question Answering Track 2004 for the source languages French and German and the target language English. We use rule-based question translation extended(More)
We describe a method which uses one or more intermediary languages in order to automatically generate translation dictionaries. Such a method could potentially be used to efficiently create translation dictionaries for language groups which have as yet had little interaction. For any given word in the source language, our method involves first translating(More)
This report describes the experiments of the University of Edinburgh and the University of Sydney at the TREC-2004 question answering evaluation exercise. Our system combines two approaches: one with deep linguistic analysis using IR on the AQUAINT corpus applied to answer extraction from text passages, and one with a shallow linguistic analysis and shallow(More)
We show how to adapt an existing monolingual open-domain QA system to perform in a cross-lingual environment, using off-the-shelf machine translation software. In our experiments we use French and Ger-man as source language, and English as target language. For answering factoid questions, our system performs with an accuracy of 16% (Ger-man to English) and(More)