Morphological Reinflection with Multiple Arguments: An Extended Annotation schema and a Georgian Case Study

David Guriel, Omer Goldman, Reut Tsarfaty

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء

ملخص

In recent years, a flurry of morphological datasets had emerged, most notably UniMorph, a multi-lingual repository of inflection tables. However, the flat structure of the current morphological annotation schema makes the treatment of some languages quirky, if not impossible, specifically in cases of polypersonal agreement, where verbs agree with multiple arguments using true affixes. In this paper we propose to address this phenomenon, by expanding the UniMorph annotation schema to hierarchical feature structure that naturally accommodates complex argument marking. We apply this extended schema to one such language, Georgian, and provide a human-verified, accurate and balanced morphological dataset for Georgian verbs. The dataset has 4 times more tables and 6 times more verb forms compared to the existing UniMorph dataset, covering all possible variants of argument marking, demonstrating the adequacy of our proposed scheme. Experiments with a standard reinflection model show that generalization is easy when the data is split at the form level, but extremely hard when splitting along lemma lines. Expanding the other languages in UniMorph to this schema is expected to improve both the coverage, consistency and interpretability of this benchmark.

اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers)
المحررونSmaranda Muresan, Preslav Nakov, Aline Villavicencio
ناشرAssociation for Computational Linguistics (ACL)
الصفحات196-202
عدد الصفحات7
رقم المعيار الدولي للكتب (الإلكتروني)9781955917223
حالة النشرنُشِر - 2022
منشور خارجيًانعم
الحدث60th Annual Meeting of the Association for Computational Linguistics, ACL 2022 - Dublin, إيرلندا
المدة: ٢٢ مايو ٢٠٢٢٢٧ مايو ٢٠٢٢

سلسلة المنشورات

الاسمProceedings of the Annual Meeting of the Association for Computational Linguistics
مستوى الصوت2
رقم المعيار الدولي للدوريات (المطبوع)0736-587X

!!Conference

!!Conference60th Annual Meeting of the Association for Computational Linguistics, ACL 2022
الدولة/الإقليمإيرلندا
المدينةDublin
المدة٢٢/٠٥/٢٢٢٧/٠٥/٢٢

ملاحظة ببليوغرافية

Publisher Copyright:
© 2022 Association for Computational Linguistics.

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