Abstract
This paper demonstrates how a graph-based semantic parser can be applied to the task of structured sentiment analysis, directly predicting sentiment graphs from text. We advance the state of the art on 4 out of 5 standard benchmark sets. We release the source code, models and predictions.
Cite
CITATION STYLE
APA
Samuel, D., Barnes, J., Kurtz, R., Oepen, S., Øvrelid, L., & Velldal, E. (2022). Direct parsing to sentiment graphs. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 470–478). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.acl-short.51
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