This paper aims to find a correlation between Information Density (ID) and extraposition of Relative Clauses (RC) in Early New High German. Since surprisal is connected to perceiving difficulties, the impact on the working memory is lower for frequent combinations with low surprisal-values than it is for rare combinations with higher surprisal-values. To improve text comprehension, producers therefore distribute information as evenly as possible across a discourse. Extraposed RC are expected to have a higher surprisal-value than embedded RC. We intend to find evidence for this idea in RC taken from scientific texts from the 17th to 19th century. We built a corpus of tokenized, lemmatized and normalized papers about medicine from the 17th and 19th century, manually determined the RC-variants and calculated a skipgram-Language Model to compute the 2-Skip-bigram surprisal of every word of the relevant sentences. A logistic regression over the summed up surprisal values shows a significant result, which indicates a correlation between surprisal values and extraposition. So, for these periods it can be said that RC are more likely to be extraposed when they have a high total surprisal value. The influence of surprisal values also seems to be stable across time. The comparison of the analyzed language periods shows no significant change.
The variation between integrated (verb-final) and independent (verb-second) causal clauses in German could depend on the amount of information conveyed in that clause. A lower amount might lead to integration, a higher amount to independence, as processing constraints might forbid integration of highly informative clauses. We use two ways to measure information amount: 1. the average ratio of given referents within the clause, 2. the cumulative surprisal of all words in the clause. Focusing on historical stages of German, a significant correlation between amount of information and integration was visible, regardless which method was used.
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