We report the results of the SemEval 2022 Task 3, PreTENS, on evaluation the acceptability of simple sentences containing constructions whose two arguments are presupposed to be or not to be in an ordered taxonomic relation.
In the spirit of further research, we plan to make this dataset and our experimental resources publicly accessible to the wider research community.
In further experiments, our evaluation shows that transformer models (BERT-m and XLM-RoBERTa-base) outperform the SVM and RF in Dutch and English languages where a different scenario is observed for Spanish.
Time series analysis can be useful to see how a given asset, security, or economy changes over time.
This is the first dataset of its kind: social media images, disaster response, and multi-task learning research.
In this study, we explore several publicly available sentiment labeled datasets and designed classifiers using both classical and deep learning algorithms.