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    <abstract>This paper presents a new dataset with Discourse Representation Structures (DRSs) annotated over naturally-occurring sentences. Importantly, these sentences are more varied in length and on average longer than those in the existing gold-standard DRS dataset, the Parallel Meaning Bank, and we show that they are therefore much harder for parsers. We argue, though, that this provides a more realistic assessment of the difficulties of DRS parsing.</abstract>
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%0 Conference Proceedings
%T The long and the short of it: DRASTIC, a semantically annotated dataset containing sentences of more natural length
%A Haug, Dag
%A Findlay, Jamie Yates
%A Yildirim, Ahmet
%Y Bonn, Julia
%Y Xue, Nianwen
%S Proceedings of the Fourth International Workshop on Designing Meaning Representations
%D 2023
%8 June
%I Association for Computational Linguistics
%C Nancy, France
%F haug-etal-2023-long
%X This paper presents a new dataset with Discourse Representation Structures (DRSs) annotated over naturally-occurring sentences. Importantly, these sentences are more varied in length and on average longer than those in the existing gold-standard DRS dataset, the Parallel Meaning Bank, and we show that they are therefore much harder for parsers. We argue, though, that this provides a more realistic assessment of the difficulties of DRS parsing.
%U https://aclanthology.org/2023.dmr-1.9
%P 89-98

Markdown (Informal)

[The long and the short of it: DRASTIC, a semantically annotated dataset containing sentences of more natural length](https://aclanthology.org/2023.dmr-1.9) (Haug et al., DMR-WS 2023)

• The long and the short of it: DRASTIC, a semantically annotated dataset containing sentences of more natural length (Haug et al., DMR-WS 2023)

ACL

• Dag Haug, Jamie Yates Findlay, and Ahmet Yildirim. 2023. The long and the short of it: DRASTIC, a semantically annotated dataset containing sentences of more natural length. In Proceedings of the Fourth International Workshop on Designing Meaning Representations, pages 89–98, Nancy, France. Association for Computational Linguistics.