Semantic Ambiguity and the Process of Generating Meaning From Print.

Pexman, Penny M.; Hino, Yasushi; Lupker, Stephen J.

doi:10.1037/0278-7393.30.6.1252

Cited by 53 publications

(134 citation statements)

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“…The absence of a number-of-senses effect on semantic classification RTs is interesting and is consistent with recent demonstrations that although ambiguity effects may not be reflected in semantic classification RTs (Pexman, Hino, & Lupker, 2004), they can be detected using neuroimaging techniques (Hargreaves et al, 2011). Of course, despite its greater objectivity, number of senses is, at best, a crude proxy for ambiguity, since it does not distinguish between related and unrelated multiple definitions.…”

Section: Discussionsupporting

confidence: 71%

Is more always better? Effects of semantic richness on lexical decision, speeded pronunciation, and semantic classification

et al. 2011

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Evidence from large-scale studies (Pexman, Hargreaves, Siakaluk, Bodner, & Pope, 2008) suggests that semantic richness, a multidimensional construct reflecting the extent of variability in the information associated with a word's meaning, facilitates visual word recognition. Specifically, recognition is better for words that (1) have more semantic neighbors, (2) possess referents with more features, and (3) are associated with more contexts. The present study extends Pexman et al. (2008) by examining how two additional measures of semantic richness, number of senses and number of associates (Pexman, Hargreaves, Edwards, Henry, & Goodyear, 2007), influence lexical decision, speeded pronunciation, and semantic classification performance, after controlling for an array of lexical and semantic variables. We found that number of features and contexts consistently facilitated word recognition but that the effects of semantic neighborhood density and number of associates were less robust. Words with more senses also elicited faster lexical decisions but less accurate semantic classifications. These findings point to how the effects of different semantic dimensions are selectively and adaptively modulated by task-specific demands.The majority of visual word recognition research has examined how lexical-level properties such as word frequency and number of letters influence performance,using tasks such as lexical decision (word/nonword discrimination), speeded pronunciation (naming words aloud), and semantic classification (e.g., classifying a word as animate or inanimate). However, there is substantial evidence that meaning-level characteristics such as imageability also affect word recognition, even after correlated lexical variables are controlled for

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Section: Discussionsupporting

confidence: 71%

Is more always better? Effects of semantic richness on lexical decision, speeded pronunciation, and semantic classification

et al. 2011

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“…That is, words with more definitions produce a response advantage in lexical decision (''does the letter string spell a word? ''), whereas the same words show a diminished effect when the semantic requirements of the task are reduced by either changing the foils to be illegal nonwords (i.e., letter strings without vowels) or changing the task to simple naming (Borowsky and Masson 1996; see also Pexman et al 2002Pexman et al , 2004. Pexman et al (2002) have also suggested that semantic richness (i.e., number of semantic features that an object has) facilitates word recognition, and their results indicate that the number of semantic features accounts for close to 50% of the variance in lexical decision reaction time, and about half of that in naming reaction time.…”

Section: Cortical Activation During Semantic Processing Of Actionmentioning

confidence: 97%

Mapping the Semantic Homunculus: A Functional and Behavioural Analysis of Overt Semantic Generation

Esopenko¹,

Borowsky

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et al. 2008

Brain Topogr

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Previous neuroanatomical research has shown that semantic processing of action-related language activates the premotor, motor, and sensory cortices somatotopically (e.g., Tettamanti et al., J Cognitive Neurosci. 2005;17(2): 273-281, using a listening task, and Hauk et al., Neuron. 2004;41:301-307 and Pulvermuller et al., Eur J Neurosci 2005;21:793-797; J Cognitive Neurosci 2005;17(6):884-892 using a silent reading task). We examined this somatotopic semantics hypothesis using an overt semantic generation task (i.e., participants generated aloud their own personal description of how they would interact with target object words), rather than semantic comprehension as examined in previous research, so as to provide a stronger test of the hypothesis under conditions that tap one's own semantic knowledge about interacting with objects. Experiment 1 used functional Magnetic Resonance Imaging (fMRI) to examine somatotopically organized activation in the premotor cortex for an overt semantic generation task, using targets that naturally involve either arm interactions or leg interactions. Consistent with previous research, our results showed that semantic processing related to object interaction involves the motor, premotor and sensory cortices in a somatotopic fashion. Previous behavioural research has shown a response advantage in lexical decision for words with multiple meanings or features, which diminishes with tasks that decrease semantic involvement (e.g., Borowsky and Masson, J Exp Psychol: Learn Memory Cognit 1996; 22(1):63-85; Pexman et al., Psychon Bull Rev 2002;9(3): 542-549). Experiment 2 evaluated whether semantic generation response times (total duration of response) display a complexity advantage (i.e., faster response times for more complex objects), and whether complexity ratings were related to the volume of brain activation during the task. Results from this behavioural experiment revealed a significant negative relationship between the total duration of response (i.e., the total amount of time taken to respond to the stimuli) and object complexity for leg objects (a semantic complexity advantage), but not for arms. This suggests that the smaller repertoire of possible interactions with leg objects requires a greater reliance on semantic knowledge in order to respond in the semantic generation task. This interpretation was further supported by a greater volume of brain activation in the premotor cortex for arm objects versus leg objects. The response times from Experiment 1 were also compared to the semantic complexity ratings gathered in Experiment 2 to determine if response times in the fMRI environment were affected by how complex an object is.

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“…Likewise, while words with more senses (i.e., more ambiguous) enjoy a processing advantage in lexical decision, the effect of ambiguity is less clear in tasks which place an emphasis on semantic activation, such as semantic categorization or semantic relatedness (i.e., are these two words related?). Specifically, there is in some cases an ambiguity disadvantage in semantic relatedness (Hoffman & Woollams, 2015;Pexman, Hino, & Lupker, 2004;Piercey & Joordens, 2000) while ambiguity effects are either inhibitory or null in semantic categorization . By ascertaining how stimulus quality and semantic variables modulate the shape, rather than just the mean, of distributions, one may find dissociations that are apparent only at the level of distributional characteristics.…”

Section: The Present Studymentioning

confidence: 99%

Semantic richness effects in lexical decision: The role of feedback

2015

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Across lexical processing tasks, it is well established that words with richer semantic representations are recognized faster. This suggests that the lexical system has access to meaning before a word is fully identified, and is consistent with a theoretical framework based on interactive and cascaded processing. Specifically, semantic richness effects are argued to be produced by feedback from semantic representations to lower-level representations. The present study explores the extent to which richness effects are mediated by feedback from lexical-to letter-level representations. In two lexical decision experiments, we examined the joint effects of stimulus quality and four semantic richness dimensions (imageability, number of features, semantic neighborhood density, semantic diversity). With the exception of semantic diversity, robust additive effects of stimulus quality and richness were observed for the targeted dimensions. Our results suggest that semantic feedback does not typically reach earlier levels of representation in lexical decision, and further reinforces the idea that task context modulates the processing dynamics of early word recognition processes.

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Semantic Ambiguity and the Process of Generating Meaning From Print.

Abstract: An ambiguity disadvantage (slower responses for ambiguous words, e.g., bank, than for unambiguous words) has been reported in semantic tasks (

Cited by 53 publications

References 54 publications

Is more always better? Effects of semantic richness on lexical decision, speeded pronunciation, and semantic classification

Is more always better? Effects of semantic richness on lexical decision, speeded pronunciation, and semantic classification

Mapping the Semantic Homunculus: A Functional and Behavioural Analysis of Overt Semantic Generation

Semantic richness effects in lexical decision: The role of feedback

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