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    <abstract>This paper describes an approach for automatic categorisation of various types of multiword expressions (MWEs) with a focus on multiword named entities (MNEs), which compose a large portion of MWEs in general. The proposed algorithm is based on a refined classification of MWEs according to their idiomaticity. While MWE categorisation can be considered as a separate and independent task, it complements the general task of MWE recognition. After outlining the method, we set up an experiment to demonstrate its performance. We use the corpus Wiki1000+ that comprises 6,311 annotated Wikipedia articles of 1,000 or more words each, amounting to 13.4 million words in total. The study also employs a large dictionary of 59,369 MWEs noun phrases (out of more than 85,000 MWEs), labelled with their respective types. The dictionary is compiled automatically and verified semi-automatically. The research presented here is based on Bulgarian although most of the ideas, the methodology and the analysis are applicable to other Slavic and possibly other European languages.</abstract>
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%0 Conference Proceedings
%T Automatic Categorisation of Multiword Expressions and Named Entities in Bulgarian
%A Stoyanova, Ivelina
%S Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014)
%D 2014
%8 September
%I Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
%C Sofia, Bulgaria
%F stoyanova-2014-automatic
%X This paper describes an approach for automatic categorisation of various types of multiword expressions (MWEs) with a focus on multiword named entities (MNEs), which compose a large portion of MWEs in general. The proposed algorithm is based on a refined classification of MWEs according to their idiomaticity. While MWE categorisation can be considered as a separate and independent task, it complements the general task of MWE recognition. After outlining the method, we set up an experiment to demonstrate its performance. We use the corpus Wiki1000+ that comprises 6,311 annotated Wikipedia articles of 1,000 or more words each, amounting to 13.4 million words in total. The study also employs a large dictionary of 59,369 MWEs noun phrases (out of more than 85,000 MWEs), labelled with their respective types. The dictionary is compiled automatically and verified semi-automatically. The research presented here is based on Bulgarian although most of the ideas, the methodology and the analysis are applicable to other Slavic and possibly other European languages.
%U https://aclanthology.org/2014.clib-1.6
%P 40-48

Markdown (Informal)

[Automatic Categorisation of Multiword Expressions and Named Entities in Bulgarian](https://aclanthology.org/2014.clib-1.6) (Stoyanova, CLIB 2014)

• Automatic Categorisation of Multiword Expressions and Named Entities in Bulgarian (Stoyanova, CLIB 2014)

ACL

• Ivelina Stoyanova. 2014. Automatic Categorisation of Multiword Expressions and Named Entities in Bulgarian. In Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014), pages 40–48, Sofia, Bulgaria. Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences.