8,134 research outputs found
Redefining part-of-speech classes with distributional semantic models
This paper studies how word embeddings trained on the British National Corpus
interact with part of speech boundaries. Our work targets the Universal PoS tag
set, which is currently actively being used for annotation of a range of
languages. We experiment with training classifiers for predicting PoS tags for
words based on their embeddings. The results show that the information about
PoS affiliation contained in the distributional vectors allows us to discover
groups of words with distributional patterns that differ from other words of
the same part of speech.
This data often reveals hidden inconsistencies of the annotation process or
guidelines. At the same time, it supports the notion of `soft' or `graded' part
of speech affiliations. Finally, we show that information about PoS is
distributed among dozens of vector components, not limited to only one or two
features
Spatial representations of numbers and letters in children
Different lines of evidence suggest that children's mental representations of numbers are spatially organized in form of a mental number line. It is, however, still unclear whether a spatial organization is specific for the numerical domain or also applies to other ordinal sequences in children. In the present study, children (n = 129) aged 8–9 years were asked to indicate the midpoint of lines flanked by task-irrelevant digits or letters. We found that the localization of the midpoint was systematically biased toward the larger digit. A similar, but less pronounced, effect was detected for letters with spatial biases toward the letter succeeding in the alphabet. Instead of assuming domain-specific forms of spatial representations, we suggest that ordinal information expressing relations between different items of a sequence might be spatially coded in children, whereby numbers seem to convey this kind of information in the most salient way
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