Abstract: The current study set out to explore the nature of online lexical access to polysemes and homonyms within L2 learners of English. Two separate experiments were conducted on 30 ESL learners and 30 native speakers of English (as a control group) using the self-paced reading method (SPR) with a view to exploring whether L2 learners of English access the meanings of the lexically-ambiguous words selectively (i.e., only the meaning primed by the preceding contextual information is accessed), exhaustively (i.e., several meanings are accessed concurrently), or in a frequency-ordered way (i.e., the most frequent meaning is accessed prior to the less frequent meanings) during sentence processing. Experiment 1 examined the effect of the lexical ambiguity type on lexical access using three categories of words: 10 polysemes, 10 homonyms, and 10 single-meaning words. Experiment 2 investigated the effect of meaning dominance on lexical processing using 20 polarized ambiguous words with dominant and subordinate meanings to find out whether the frequency of meaning affects the latency of lexical access. The results from the two experiments showed that neither lexical ambiguity type nor meaning dominance significantly affected the processing latencies of the non-native speakers (NNSs) and native speakers (NSs) in context. The results suggest that the nature of lexical access to the meanings of the lexically ambiguous words in L2 learners is selective as long as the word is presented in a sentential context.

The most frequently used words in English are highly ambiguous; for example, Webster's Ninth New Collegiate Dictionary lists 94 meanings for the word "run" as a verb alone. Yet people rarely notice this ambiguity. Solving this puzzle has commanded the efforts of cognitive scientists for many years. The solution most often identified is "context": we use the context of utterance to determine the proper meanings of words and sentences. The problem then becomes specifying the nature of context and how it interacts with the rest of an understanding system. The difficulty becomes especially apparent in the attempt to write a computer program to understand natural language. Lexical ambiguity resolution (LAR), then, is one of the central problems in natural language and computational semantics research. A collection of the best research on LAR available, this volume offers eighteen original papers by leading scientists. Part I, Computer Models, describes nine attempts to discover the processes necessary for disambiguation by implementing programs to do the job. Part II, Empirical Studies, goes into the laboratory setting to examine the nature of the human disambiguation mechanism and the structure of ambiguity itself. A primary goal of this volume is to propose a cognitive science perspective arising out of the conjunction of work and approaches from neuropsychology, psycholinguistics, and artificial intelligence--thereby encouraging a closer cooperation and collaboration among these fields. Lexical Ambiguity Resolution is a valuable and accessible source book for students and cognitive scientists in AI, psycholinguistics, neuropsychology, or theoretical linguistics.