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    <abstract>The PARSEME (Parsing and Multiword Expressions) project proposes multilingual corpora annotated for multiword expressions (MWEs). In this case study, we focus on the Turkish corpus of PARSEME. Turkish is an agglutinative language and shows high inflection and derivation in word forms. This can cause some issues in terms of automatic morphosyntactic annotation. We provide an overview of the problems observed in the morphosyntactic annotation of the Turkish PARSEME corpus. These issues are mostly observed on the lemmas, which is important for the approximation of a type of an MWE. We propose modifications of the original corpus with some enhancements on the lemmas and parts of speech. The enhancements are then evaluated with an identification system from the PARSEME Shared Task 1.2 to detect MWEs, namely Seen2Seen. Results show increase in the F-measure for MWE identification, emphasizing the necessity of robust morphosyntactic annotation for MWE processing, especially for languages that show high surface variability.</abstract>
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%0 Conference Proceedings
%T Enhancing the PARSEME Turkish Corpus of Verbal Multiword Expressions
%A Ozturk, Yagmur
%A Hadj Mohamed, Najet
%A Lion-Bouton, Adam
%A Savary, Agata
%Y Bhatia, Archna
%Y Cook, Paul
%Y Taslimipoor, Shiva
%Y Garcia, Marcos
%Y Ramisch, Carlos
%S Proceedings of the 18th Workshop on Multiword Expressions @LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F ozturk-etal-2022-enhancing
%X The PARSEME (Parsing and Multiword Expressions) project proposes multilingual corpora annotated for multiword expressions (MWEs). In this case study, we focus on the Turkish corpus of PARSEME. Turkish is an agglutinative language and shows high inflection and derivation in word forms. This can cause some issues in terms of automatic morphosyntactic annotation. We provide an overview of the problems observed in the morphosyntactic annotation of the Turkish PARSEME corpus. These issues are mostly observed on the lemmas, which is important for the approximation of a type of an MWE. We propose modifications of the original corpus with some enhancements on the lemmas and parts of speech. The enhancements are then evaluated with an identification system from the PARSEME Shared Task 1.2 to detect MWEs, namely Seen2Seen. Results show increase in the F-measure for MWE identification, emphasizing the necessity of robust morphosyntactic annotation for MWE processing, especially for languages that show high surface variability.
%U https://aclanthology.org/2022.mwe-1.14
%P 100-104

Markdown (Informal)

[Enhancing the PARSEME Turkish Corpus of Verbal Multiword Expressions](https://aclanthology.org/2022.mwe-1.14) (Ozturk et al., MWE 2022)

• Enhancing the PARSEME Turkish Corpus of Verbal Multiword Expressions (Ozturk et al., MWE 2022)

ACL

• Yagmur Ozturk, Najet Hadj Mohamed, Adam Lion-Bouton, and Agata Savary. 2022. Enhancing the PARSEME Turkish Corpus of Verbal Multiword Expressions. In Proceedings of the 18th Workshop on Multiword Expressions @LREC2022, pages 100–104, Marseille, France. European Language Resources Association.