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 language | English |
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| Title of host publication | CoNLL 2019 - 23rd Conference on Computational Natural Language Learning, Proceedings of the Conference |
| Publisher | Association for Computational Linguistics |
| Pages | 174-185 |
| Number of pages | 12 |
| ISBN (Electronic) | 9781950737727 |
| State | Published - 2019 |
| Event | 23rd Conference on Computational Natural Language Learning, CoNLL 2019 - Hong Kong, China Duration: 3 Nov 2019 → 4 Nov 2019 |
Publication series
| Name | CoNLL 2019 - 23rd Conference on Computational Natural Language Learning, Proceedings of the Conference |
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Conference
| Conference | 23rd Conference on Computational Natural Language Learning, CoNLL 2019 |
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| Country/Territory | China |
| City | Hong Kong |
| Period | 3/11/19 → 4/11/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computational Linguistics.