Ambiguity Advantage Revisited: Two Meanings are Better than One When Accessing Chinese Nouns

Abstract

This paper revisits the effect of lexical ambiguity in word recognition, which has been controversial as previous research reported advantage, disadvantage, and null effects. We discuss factors that were not consistently treated in previous research (e.g., the level of lexical ambiguity investigated, parts of speech of the experimental stimuli, and the choice of non-words) and report on a lexical decision experiment with Chinese nouns in which ambiguous nouns with homonymic and/or metaphorical meanings were contrasted with unambiguous nouns. An ambiguity advantage effect was obtained-Chinese nouns with multiple meanings were recognized faster than those with only one meaning. The results suggested that both homonymic and metaphorical meanings are psychologically salient semantic levels actively represented in the mental lexicon. The results supported a probability-based model of random lexical access with multiple meanings represented by separate semantic nodes. We further discuss these results in terms of lexical semantic representation and how different experimental paradigms result in different ambiguity effects in lexical access.

The Organization of the Senses of Polysemy in Japanese EFL Learners’ Mental Lexicon

“…More specifically, the upper group tended to put A 1 , A 2 , and A 3 , which were the same in each target context in this study, into the same category. However, considering that native speakers still produced a different number of senses from the dictionary's definition (Lin & Ahrens, 2010), categorization in the mental lexicon might not be able to be perfectly the same as Furthermore, the upper group's categories were more converged than the lower groups' classification, meaning that the participants in the upper group classified the target contexts similarly; on the other hand, the lower group's classifications had more variation, even though both groups answered regarding the target context and showing understanding to the same degree (see Table 3). …”

“…That is, even if a polysemous word has more multiple senses than another polysemous word, the times required for lexical access between them were not different. Lin and Ahrens (2010) also showed that the number of senses that their participants produced differed from the number of senses described in dictionaries. These findings indicate that the number of senses in dictionaries does not seem to directly reflect the mental lexicon.…”

Exhaustive semantic activation for reading ambiguous verbs in Chinese sentences

“…One classic example of such an effect is the so-called number of meaning effect, according to which lexical forms associated with greater numbers of meanings are more quickly recognized than those associated with fewer or single meanings (Borowsky and Masson 1996;Hino and Lupker 1996;Hino et al 2006;Jastrzembski 1981;Jastrzembski and Stanners 1975;Kellas et al 1988;Lin and Ahrens 2010;Millis and Button 1989;Rubenstein et al 1970, c.f., Rodd et al 2002. A fundamental question that has recently regained much attention concerns the relation between lexical processing and how lexical ambiguity is defined (e.g., Klepousniotou and Baum 2007;Klepousniotou et al 2012).…”

Finding What You Expect to See: Theoretical Modeling in Psycholinguistics

“…Research in examining how lexical ambiguity is resolved in on-going sentence processing usually focuses on the type of ambiguity found in the example (4), what Ahrens et al (1998) call 'active complexity (Research that looks at what Ahrens et al (1998) refer to as latent complexity, as in example (5), is usually examined with the aid of lexical decision tasks run independent of on-going sentence processing (for example, see Lin and Ahrens, 2010)'.…”

“…This would allow researchers to first test the working memory span of their participants and modify their visual probe position accordingly b) A database indicating the word senses for each lexical ambiguity and how strongly associated that sense is with the lexical item. This strength association could be calculated on the basis of the first sense a large sample of participants thinks of, or it could be based on the average percentage of that sense for all responses (Lin and Ahrens, 2010 for a further discussion of this issue and related literature). These participants might also be grouped into high and low verbal IQ, as low verbal IQ participants may generate fewer senses.…”