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Between classical symbolic word sense disambiguation (wsd) using explicit deep semantic representations of sentences and texts and statistical wsd using word co-occurrence information, there is a recent tendency towards mediating methods. Similar to so-called lightweight semantics (Marek, 2009) we suggest to only make sparse use of semantic information. We describe an approximation model based upon flat underspecified discourse representation structures (FUDRSs, cf. Eberle, 2004) that weighs knowledge about context structure, lexical semantic restrictions and interpretation preferences. We give a catalogue of guidelines for human annotation of texts by corresponding indicators. Using this, the reliability of an analysis tool that implements the model can be tested with respect to annotation precision and disambiguation prediction and how both can be improved by bootstrapping the knowledge of the system using corpus information. For the balanced test corpus considered the recognition rate of the preferred reading is 80-90% (depending on the smoothing of parse errors).
Electronic dictionaries should support dictionary users by giving them guidance in text production and text reception, alongside a user-definable offer of lexicographic data for cognitive purposes. In this article, we sketch the principles of an interactive and dynamic electronic dictionary aimed at text production and text reception guiding users in innovative ways, especially with respect to difficult, complicated or confusing issues. The lexicographer has to do a very careful analysis of the nature of the possible problems to suggest an optimal solution for a specific problem. We are of the opinion that there are numerous complex situations where users need more detailed support than currently available in e-dictionaries, enabling them to make valid and correct choices. For highly complex situations, we suggest guidance through a decision tree-like device. We assume that the solutions proposed here are not specific to one language only but can, after careful analysis, be applied to e-dictionaries in different languages across the world.