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This paper deals with a specific type of lexeme, namely binary preposition-noun combinations containing temporal references like am Ende [at (the) end] or für Sekunden [for seconds]. The main characteristic of these combinations is the recurrent internal zero gap. Despite the fact that the omission of the determiner can often be explained by grammatical rules, the zero gaps indicate a higher degree of lexicalization. Therefore, we interpret these expressions as minimal phraseological units with holistic meanings and functions. The corpusdriven exploration of typical context patterns (e.g. using collocation profiles and the lexpan slot filler analysis) shows that a) even such minimal expressions are based on semi-abstract schemes and b) temporal expressions can also fulfill modal or discursive functions, usually with fuzzy borders and overlapping structures. In the case of modalization or pragmatization one can regard such PNs as distinct lexicon entries.
Complement phrases are essential for constructing well-formed sentences in German. Identifying verb complements and categorizing complement classes is challenging even for linguists who are specialized in the field of verb valency. Against this background, we introduce an ML-based algorithm which is able to identify and classify complement phrases of any German verb in any written sentence context. We use a large training set consisting of example sentences from a valency dictionary, enriched with POS tagging, and the ML-based technique of Conditional Random Fields (CRF) to generate the classification models.
This paper presents C-WEP, the Collection of Writing Errors by Professionals Writers of German. It currently consists of 245 sentences with grammatical errors. All sentences are taken from published texts. All authors are professional writers with high skill levels with respect to German, the genres, and the topics. The purpose of this collection is to provide seeds for more sophisticated writing support tools as only a very small proportion of those errors can be detected by state-of-the-art checkers. C-WEP is annotated on various levels and freely available.
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.
Pragmatics and grammar
(2011)