In 2005, DeLong, Urbach, and Kutas took advantage of the a/an English indefinite article phonological alternation and the sensitivities of the N400 ERP component to show that readers can neurally preactivate individual words of a sentence (including nouns and their prenominal indefinite articles) in a graded fashion with a likelihood estimated from the words' offline probabilities as sentence c...

We report on the large-scale acquisition of class attributes with and without the use of lists of representative instances, as well as the discovery of unary attributes, such as typically expressed in English through prenominal adjectival modification. Our method employs a system based on compositional language processing, as applied to the British National Corpus. Experimental results suggest ...

In the paper we analyse Polish descriptive adjectives which occur in domain related texts. The experiments were done on data obtained from hospital discharge records. Prenominal adjectives selected from these texts were filtered out of presumably relative adjectives and clustered on the basis of a set of context related features and interword relations derived from Wordnet. We tested if this pr...

In this article, we propose the use of suffix arrays to implement n-gram language models with practically unlimited size n. These unbounded n-grams are called ∞-grams. This approach allows us to use large contexts efficiently to distinguish between different alternative sequences while applying synchronous back-off. From a practical point of view, the approach has been applied within the contex...

We report on chunk tagging methods for German that recognize complex non-verbal phrases using structural chunk tags with Conditional Random Fields (CRFs). This state-of-the-art method for sequence classification achieves 93.5% accuracy on newspaper text. For the same task, a classical trigram tagger approach based on Hidden Markov Models reaches a baseline of 88.1%. CRFs allow for a clean and p...