  Misinformation spreading in mainstream and social media has been misleading
users in different ways. Manual detection and verification efforts by
journalists and fact-checkers can no longer cope with the great scale and quick
spread of misleading information. This motivated research and industry efforts
to develop systems for analyzing and verifying news spreading online. The
SemEval-2023 Task 3 is an attempt to address several subtasks under this
overarching problem, targeting writing techniques used in news articles to
affect readers' opinions. The task addressed three subtasks with six languages,
in addition to three ``surprise'' test languages, resulting in 27 different
test setups. This paper describes our participating system to this task. Our
team is one of the 6 teams that successfully submitted runs for all setups. The
official results show that our system is ranked among the top 3 systems for 10
out of the 27 setups.
