Number of Meanings and Number of Senses: An ERP Study of Sublexical Ambiguities in Reading Chinese Disyllabic Compounds.

Hsu-Wen Huang,Chia-Ying Lee

doi:10.3389/fpsyg.2018.00324

Abstract

In English, an extensive body of work in both behavioral and neuropsychological domains has produced strong evidence that homonymy (words with many distinct meanings) and polysemy (many related senses) are represented, retrieved, and processed differently in the human brain. In Chinese, most words are compounds, and the constituent characters within a compound word can have different meanings and/or related senses on their own. Thus, in order to resolve lexical ambiguity in Chinese, one has to consider the composition of constituent characters, as well as how they contribute to whole word reading, known as “sublexical ambiguity.” This study investigates how two types of sublexical ambiguity affect Chinese word processing. The number of meanings (NOM) and the number of senses (NOS) corresponding to the first character of Chinese compounds were manipulated in a lexical decision task. The interactions between NOM and NOS were observed in both behavioral results and N400s, in which NOM disadvantage effect was found for words with few-senses only. On the other hand, the NOS facilitation effect was significant for words with multiple-meanings (NOM > 1) only. The sublexical ambiguity disadvantage suggested that semantically unrelated morphemes are represented as separate entries. For characters with multiple meanings, one orthographic form is associated with more than one morphemic representation. In contrast, the sublexical sense advantage supported the idea that semantically related senses that shared a morphological root are represented within a single entry. The more senses listed in a morphological root, the stronger representation will be formed. These results suggest that two types of sublexical ambiguities are represented and processed differently in Chinese word recognition models and also demonstrate that how they interact with each other in the mental lexicon.

Highlights

“Words and meanings do not always form one-to-one correspondences.” The majority of words are, extensively associated with multiple meanings — which has been referred to as lexical ambiguity
In the visual word recognition literature, studies have reported that words with multiple meanings yield faster response times than words with few meanings, when all words are matched for frequency (Rubenstein et al, 1970; Jastrzembski, 1981; Kellas et al, 1988; Millis and Button, 1989; Borowsky and Masson, 1996; Hino and Lupker, 1996; Azuma and Van Orden, 1997; Lichacz et al, 1999), the so-called “ambiguity advantage effect.”
The number of meanings (NOM) main effect was marginally significant in the participants analysis [F1(1,24) = 3, p = 0.09], the differences in the items analysis was not significant [F2(1,29) = 0.4], but the result showed the same trend as in the participants analysis, such that words with multiple meanings were responded to slower than words with one meaning

Summary

Introduction

“Words and meanings do not always form one-to-one correspondences.” The majority of words are, extensively associated with multiple meanings — which has been referred to as lexical ambiguity. Two different types of ambiguity have been distinguished Homonymous words, such as bark, have two (or more) semantically unrelated meanings associated with a single word form. To further distinguish the effects of having multiple unrelated meanings (homonymous words) from the effects of having multiple related senses (polysemous words), Rodd et al (2002) reanalyzed both high- and low- ambiguous words used in previous studies (e.g., Millis and Button, 1989; Borowsky and Masson, 1996; Azuma and Van Orden, 1997). Words with many senses are semantically richer, and easier to recognize than words with fewer senses (Rodd et al, 2002)

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