How meaning similarity influences ambiguous word processing: the current state of the literature
- PMID: 24889119
- PMCID: PMC5114844
- DOI: 10.3758/s13423-014-0665-7
How meaning similarity influences ambiguous word processing: the current state of the literature
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.
Figures
References
-
- Adriaens G, Small SL, Cottrell GW, Tanenhaus MK. Lexical ambiguity resolution: perspectives from psycholinguistics, neuropsychology, and artificial intelligence. San Mateo, CA: Morgan Kaufmann Publishers; 1988.
-
- Armstrong BC. Doctor of Philosophy. Carnegie Mellon University; 2012. The Temporal dynamics of word comprehension and response selection: Computational and behavioral studies.
-
- Armstrong BC, Plaut DC. Settling dynamics in distributed networks explain task differences in semantic ambiguity effects: Computational and behavioral evidence. Paper presented at the Proceedings of the 30th Annual Conference of the Cognitive Science Society.2008.
-
- Armstrong BC, Plaut DC. Inducing homonymy effects via stimulus quality and (not) nonword difficulty: Implications for models of semantic ambiguity and word recognition. Paper presented at the Proceedings of the 33rd Annual Conference of the Cognitive Science Society.2011.
-
- Azuma T, Van Orden GC. Why SAFE Is Better Than FAST: The Relatedness of a Word’s Meanings Affects Lexical Decision Times. Journal of Memory and Language. 1997;36(4):484–504. doi: 10.1006/jmla.1997.2502. - DOI
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources