Made for each other: Broad-coverage semantic structures meet preposition supersenses

Jakob Prange, Nathan Schneider, Omri Abend

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013) is a typologically-informed, broad-coverage semantic annotation scheme that describes coarse-grained predicate-argument structure but currently lacks semantic roles. We argue that lexicon-free annotation of the semantic roles marked by prepositions, as formulated by Schneider et al. (2018), is complementary and suitable for integration within UCCA. We show empirically for English that the schemes, though annotated independently, are compatible and can be combined in a single semantic graph. A comparison of several approaches to parsing the integrated representation lays the groundwork for future research on this task.

Original languageAmerican English
Title of host publicationCoNLL 2019 - 23rd Conference on Computational Natural Language Learning, Proceedings of the Conference
PublisherAssociation for Computational Linguistics
Pages174-185
Number of pages12
ISBN (Electronic)9781950737727
StatePublished - 2019
Event23rd Conference on Computational Natural Language Learning, CoNLL 2019 - Hong Kong, China
Duration: 3 Nov 20194 Nov 2019

Publication series

NameCoNLL 2019 - 23rd Conference on Computational Natural Language Learning, Proceedings of the Conference

Conference

Conference23rd Conference on Computational Natural Language Learning, CoNLL 2019
Country/TerritoryChina
CityHong Kong
Period3/11/194/11/19

Bibliographical note

Funding Information:
We would like to thank Daniel Hershcovich and Adi Shalev for letting us use their code and helping fix bugs; Sean MacAvaney and Vivek Sriku-mar for assistance with computing resources; as well as three anonymous reviewers for their helpful comments and suggestions. This research was supported in part by NSF award IIS-1812778 and grant 2016375 from the United States–Israel Binational Science Foundation (BSF), Jerusalem, Israel.

Funding Information:
We would like to thank Daniel Hershcovich and Adi Shalev for letting us use their code and helping fix bugs; Sean MacAvaney and Vivek Srikumar for assistance with computing resources; as well as three anonymous reviewers for their helpful comments and suggestions. This research was supported in part by NSF award IIS-1812778 and grant 2016375 from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Israel.

Publisher Copyright:
© 2019 Association for Computational Linguistics.

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