News headlines serve as condensed gateways to information, yet they often harbor layers of ambiguity, influencing how readers interpret and engage with news. This study scrutinizes the pervasive presence of lexical ambiguity within the headlines of CNN World, employing a semantic lens to unravel its multifaceted nature. Through a meticulous analysis of linguistic structures and contextual nuances, the research dissects various instances of ambiguity, delineating the intricate interplay between words, phrases, and diverse interpretations. This research aims to identify the types of lexical ambiguity and analyze the meanings of lexical ambiguity in news headlines from CNN World. The theory used in this research is the theory from Kreidler (2002) and Lyons (1996). The research used a descriptive qualitative method to classify and the data source which taken from CNN World news headlines published in 2023. The result of research, there are 4 homonyms (60%) and 2 polysemy (40%) found in 6 news headlines from CNN. The most common form was homonymy. And the meaning occurs in this research is contextual meaning.
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