Distinguishing the Types of Coordinated Verbs with a Shared Argument by means of New ZeugBERT Language Model and ZeugmaDataset
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Proceedings |
| Conference | Towards a Knowledge-Aware AI : SEMANTiCS 2022 — Proceedings of the 18th International Conference on Semantic Systems, 13-15 September 2022, Vienna, Austria |
| MU Faculty or unit | |
| Citation | |
| web | https://ebooks.iospress.nl/volumearticle/60724 |
| Doi | http://dx.doi.org/10.3233/SSW220022 |
| Keywords | natural language understanding; coordinated verbs with shared argument; zeugma; BERT language model; dataset |
| Description | Sentences where two verbs share a single argument represent a complex and highly ambiguous syntactic phenomenon. The argument sharing relations must be considered during the detection process from both a syntactic and semantic perspective. Such expressions can represent ungrammatical constructions, denoted as zeugma, or idiomatic elliptical phrase combinations. Rule-based classification methods prove ineffective because of the necessity to reflect meaning relations of the analyzed sentence constituents. This paper presents the development and evaluation of ZeugBERT, a language model tuned for the sentence classification task using a pre-trained Czech transformer model for language representation. The model was trained with a newly prepared dataset, which is also published with this paper, of 7,849 Czech sentences to classify Czech syntactic structures containing coordinated verbs that share a valency argument (or an optional adjunct) in the context of coordination. ZeugBERT here reaches $88\,\%$ of test set accuracy. The text describes the process of the new dataset creation and annotation, and it offers a detailed error analysis of the developed classification model. |
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