SemEval 2022 Task 10: Structured Sentiment Analysis
Jeremy Barnes, Laura Oberlaender, Enrica Troiano, Andrey Kutuzov, Jan Buchmann, Rodrigo Agerri, Lilja Øvrelid, Erik Velldal
Abstract
In this paper, we introduce the first SemEval shared task on Structured Sentiment Analysis, for which participants are required to predict all sentiment graphs in a text, where a single sentiment graph is composed of a sentiment holder, target, expression and polarity. This new shared task includes two subtracks (monolingual and cross-lingual) with seven datasets available in five languages, namely Norwegian, Catalan, Basque, Spanish and English. Participants submitted their predictions on a held-out test set and were evaluated on Sentiment Graph F1 . Overall, the task received over 200 submissions from 32 participating teams. We present the results of the 15 teams that provided system descriptions and our own expanded analysis of the test predictions.- Anthology ID:
- 2022.semeval-1.180
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1280–1295
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.180
- DOI:
- 10.18653/v1/2022.semeval-1.180
- Cite (ACL):
- Jeremy Barnes, Laura Oberlaender, Enrica Troiano, Andrey Kutuzov, Jan Buchmann, Rodrigo Agerri, Lilja Øvrelid, and Erik Velldal. 2022. SemEval 2022 Task 10: Structured Sentiment Analysis. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1280–1295, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- SemEval 2022 Task 10: Structured Sentiment Analysis (Barnes et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2022.semeval-1.180.pdf
- Data
- MPQA Opinion Corpus, MultiBooked