Abstract
The Semantic Web came with the prospect of once providing amounts of information just as immense as those now available from the Internet, ready for evaluation and analysis by machines. About a decade later, more and more data hubs (a data hub is comparable to a web site) emerged that provide information free of charge. Massive amounts of such information, also called Linked Open Data (LOD), make the vision of the Semantic Web come to life. As an example, DBpedia – by harvesting information from Wikipedia – already contains hundreds of millions of general knowledge facts. Such data can be used to conveniently make information of general interest available to the public. Above this, the structure of this information and the fact that it is present in machine readable form renders possibly more structured ways of information access. One of these technologies is Question Answering (QA) – a task that always hinged on the availability of massive amounts of information. This paper reports on our approach to implementing a QA system backed by Linked Open Data. The QA system is part of the Alexandria use case.
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An example of this pattern is DBpedia. It is fair to say that this structure arises from the infoboxes being harvested, not a general misconception, though.
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For German tokenization and POS-Tagging we use OpenNLP with some pre-trained models. (http://incubator.apache.org/opennlp/)
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Wendt, M., Gerlach, M., Düwiger, H. (2014). Ask Like an Egyptian: Question Answering in the Alexandria Use Case. In: Wahlster, W., Grallert, HJ., Wess, S., Friedrich, H., Widenka, T. (eds) Towards the Internet of Services: The THESEUS Research Program. Cognitive Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-06755-1_23
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