Bootstrapping a Database of German Multi-word Expressions

Abstract

We pre-classified 32,000 entries from the {Wörterbuch der deutschen Idiomatik} (Schemann 1993) using an inductive description of POS sequences in conjunction with a Brill Tagger trained on manually tagged idiomatic entries. This process assigned categories to 86% of entries with 88% accuracy. Further manual classification resulted in a database of multi-word expressions where each entry is associated with a sequence of POS-tag/token pairs. The second phase of our project, currently underway, addresses the association of a sequence of POS-tag/token pairs with a corpus example. To this end, we generate a weighted finite state transducer from the sequences for each entry and apply a finite state filter to the corpus. The filter will extract those sequences in the corpus that correspond to the longest match of the multi-word expression.

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