Publication details

Discovering Continuous Multi-word Expressions in Czech

Investor logo
Authors

NEVĚŘILOVÁ Zuzana

Year of publication 2018
Type Article in Periodical
Magazine / Source Computación y Sistemas
MU Faculty or unit

Faculty of Informatics

Citation
web http://doi.org/10.13053/CyS-22-3-3022
Doi http://dx.doi.org/10.13053/CyS-22-3-3022
Keywords Multiword expression; Multi-word expression; MWE; MWE discovery; inter-lingual homographs
Description Multi-word expressions frequently cause incorrect annotations in corpora, since they often contain foreign words or syntactic anomalies. In case of foreign material, the annotation quality depends on whether the correct language of the sequence is detected. In case of inter-lingual homographs, this problem becomes difficult. In the previous work, we created a dataset of Czech continuous multi-word expressions (MWEs). The candidates were discovered automatically from Czech web corpus considering their orthographic variability. The candidates were classified and annotated manually. Afterwards, the dataset was extended automatically by generating all word forms of those MWEs that were annotated as nouns. In this work, we used the dataset as positive examples, we filtered out negative examples from the MWE candidates. We trained a classifier with mean accuracy 92.7%. We have shown that the combined approach slightly outperforms approaches concerning only association measures mainly on MWEs containing inter-lingual homographs and out-of-vocabulary words. The discovery methods can be applied to other languages which encounter orthographic variability in web corpora.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.

More info