SemEval 2022 Task 10: Structured Sentiment Analysis
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Sentiment AnalysisSimilar Papers 제목 키워드 기반
ISCAS at SemEval-2022 Task 10: An Extraction-Validation Pipeline for Structured Sentiment Analysis
ISCAS participated in both sub-tasks in SemEval-2022 Task 10: Structured Sentiment competition. We design an extraction-validation pipeline architecture to tackle both monolingual and cross-lingual sub-tasks. Experimenta…
Sentiment AnalysisUFRGSent at SemEval-2022 Task 10: Structured Sentiment Analysis using a Question Answering Model
This paper describes the system submitted by our team (UFRGSent) to SemEval-2022 Task 10: Structured Sentiment Analysis. We propose a multilingual approach that relies on a Question Answering model to find tuples consist…
PositionQuestion AnsweringSentiment AnalysisSentiment ClassificationOPI at SemEval-2022 Task 10: Transformer-based Sequence Tagging with Relation Classification for Structured Sentiment Analysis
This paper presents our solution for SemEval-2022 Task 10: Structured Sentiment Analysis. The solution consisted of two modules: the first for sequence tagging and the second for relation classification. In both modules …
Relation ClassificationSentiment AnalysisAMEX AI Labs at SemEval-2022 Task 10: Contextualized fine-tuning of BERT for Structured Sentiment Analysis
We describe the work carried out by AMEX AI Labs on the structured sentiment analysis task at SemEval-2022. This task focuses on extracting fine grained information w.r.t. to source, target and polar expressions in a giv…
Sentiment AnalysisECNU_ICA at SemEval-2022 Task 10: A Simple and Unified Model for Monolingual and Crosslingual Structured Sentiment Analysis
Sentiment analysis is increasingly viewed as a vital task both from an academic and a commercial standpoint. In this paper, we focus on the structured sentiment analysis task that is released on SemEval-2022 Task 10. The…
Event ExtractionSentiment Analysis