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Updated: Apr 28, 2026

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
Published on: June 29, 2021
How meaning similarity influences ambiguous word processing: the current state of the literature
Charles M Eddington1, Natasha Tokowicz
1Learning Research and Development Center, University of Pittsburgh, 3939 O'Hara St., Room 651, Pittsburgh, PA, 15260, USA.
Abstract:
The majority of words in the English language do not correspond to a single meaning, but rather correspond to two or more unrelated meanings (i.e., are homonyms) or multiple related senses (i.e., are polysemes). It has been proposed that the different types of "semantically-ambiguous words" (i.e., words with more than one meaning) are processed and represented differently in the human mind. Several review papers and books have been written on the subject of semantic ambiguity (e.g., Adriaens, Small, Cottrell, & Tanenhaus, 1988; Burgess & Simpson, 1988; Degani & Tokowicz, 2010; Gorfein, 1989, 2001; Simpson, 1984). However, several more recent studies (e.g., Klein & Murphy, 2001; Klepousniotou, 2002; Klepousniotou & Baum, 2007; Rodd, Gaskell, & Marslen-Wilson, 2002) have investigated the role of the semantic similarity between the multiple meanings of ambiguous words on processing and representation, whereas this was not the emphasis of previous reviews of the literature. In this review, we focus on the current state of the semantic ambiguity literature that examines how different types of ambiguous words influence processing and representation. We analyze the consistent and inconsistent findings reported in the literature and how factors such as semantic similarity, meaning/sense frequency, task, timing, and modality affect ambiguous word processing. We discuss the findings with respect to recent parallel distributed processing (PDP) models of ambiguity processing (Armstrong & Plaut, 2008, 2011; Rodd, Gaskell, & Marslen-Wilson, 2004). Finally, we discuss how experience/instance-based models (e.g., Hintzman, 1986; Reichle & Perfetti, 2003) can inform a comprehensive understanding of semantic ambiguity resolution.
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