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To reach even language users not acquainted to the use of grammars the Institut für Deutsche Sprache in Mannheim (Germany) looked for new ways to handle grammatical problems. Instead of confronting users with abstractions frequent difficulties of German grammar are introduced in form of exemplary questions like „Which form should be used or preferred: Anfang dieses Jahre or Anfang diesen Jahres? Looking through the long list of such questions even laymen may find solutions of grammatical problems they might not be able to formulate as such.
Grammatiktheoretische Forschung, das hat die jüngste IDS-Jahrestagung wieder einmal plastisch vor Augen geführt, muss gedacht werden als zähes Ringen zweier grundsätzlich antagonistischer Prinzipien: Der reichhaltigen Fülle sprachlicher Okkurrenzen, deren gründlicher Auslotung ein beträchtlicher Teil der gegenwärtigen sprachtheoretisch und sprachtechnologisch ausgerichteten Anstrengung gewidmet ist, muss stets der Versuch gegenüberstehen, diese überbordende Varianz abstrahierend und generalisierend einzudämmen – ohne dabei die empirischen Befunde übermäßig und unzulässig zu nivellieren.
Grammars even trying to be as comprehensible as possible hardly avoid using technical terms unknown to novices. To overcome these inconveniencies, the grammatical information system grammis of the Institut für Deutsche Sprache incorporated a glossary specialized on terms used within the system. This glossary - actually named Grammatische Grundbegriffe (elementary terms of grammar) and tied by hyperlinks to technical terms in the core grammar' of grammis - offers short and simple explanations mainly by means of exemplification. The idea is to provide the users with provisional understanding to get along while following the main themes they are interested in. Explicitly, the glossary is not a stand-alone dictionary of grammatical terms, and it should not be regarded as one.
In this feasibility study we aim at contributing at the practical use of domain ontologies for hypertext classification by introducing an algorithm generating potential keywords. The algorithm uses structural markup information and lemmatized word lists as well as a domain ontology on linguistics. We present the calculation and ranking of keyword candidates based on ontology relationships, word position, frequency information, and statistical significance as evidenced by log-likelihood tests. Finally, the results of our machine-driven classification are validated empirically against manually assigned keywords.