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2020 | 6 | 60-73

Article title

Word-based largest chunks for Agreement Groups processing: Cross-linguistic observations

Content

Title variants

PL
Word-based largest chunks for Agreement Groups processing: Cross-linguistic observations

Languages of publication

EN

Abstracts

EN
The present study reports results from a series of computer experiments seeking to combine word-based Largest Chunk (LCh) segmentation and Agreement Groups (AG) sequence processing. The AG model is based on groups of similar utterances that enable combinatorial mapping of novel utterances. LCh segmentation is concerned with cognitive text segmentation, i.e. with detecting word boundaries in a sequence of linguistic symbols. Our observations are based on the text of Le petit prince (The little prince) by Antoine de Saint-Exupéry in three languages: French, English, and Hungarian. The data suggest that word-based LCh segmentation is not very efficient with respect to utterance boundaries, however, it can provide useful word combinations for AG processing. Typological differences between the languages are also reflected in the results.

Year

Volume

6

Pages

60-73

Physical description

Dates

published
2020-12-30

Contributors

References

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.ojs-doi-10_31743_lingbaw_11831
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