On the Meaning of Words and Dinosaur Bones: Lexical Knowledge Without a Lexicon

By Jeffrey L. Elman. Cognitive Sciences, 2009

383 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cultural Studies, Language and Linguistics

View Paper: https://www.semanticscholar.org/paper/0e8415b2082b0d9a4626f58a92401279c0d2df9b

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Citations in the corpus

Polysemy and word meaning: an account of lexical meaning for different kinds of content words (2018, background): “For instance, cut surely has lots of senses (Elman, 2009), but it is not clear whether in cut the grass and cut the cake, cut expresses different senses, something that does not seem to happen in metonymy-based polysemy.”
Getting real about semantic illusions: rethinking the functional role of the P600 in language comprehension. (2012, result): “This is consistent with theoretical proposals on the organization of the mental lexicon (Elman, 2004, 2009; Pulvermüller, 1999, 2001; Rogers and McClelland, 2004), with theories of memory (Gillund and Shiffrin, 1984; Hintzman, 1988; Ratcliff, 1978) and with the general idea that language processing…”
The Centrality of Language in Human Cognition (2016, background): “This position is best articulated by Elman (2004, 2009), who, drawing on earlier work by Rumelhart (1979) , contrasts the view of words as cues to meaning to the standard position of words having (i.e., mapping onto) meanings:”
How Language Programs the Mind (2016, background): “So, rather than viewing words as reflexively activating discrete bundles of features, it is more useful to think of words as inputs (cues) to a dynamic system that is always transitioning from one state to the next, the implication being that word meanings are intrinsically context-dependent (Casasa”
Digging up the building blocks of language: Age-of-acquisition effects for multiword phrases (2017, background): “This idea is found in linguistic approaches that emphasize the role of constructions in language (Culicover & Jackendoff, 2005; Goldberg, 2006; Langacker, 1987) and is advocated in single-system models of language which posit that all linguistic material – whether it is words or larger sequences – i”
The minority report: some common assumptions to reconsider in the modelling of the brain and behaviour (2016, background): “…behaviour such as language learning and production in shallow uniform distributed architectures (e.g. in Simple Recurrent Networks; Chang, 2002; Elman, 1990, 2009; or Echo State Networks; Tong, Bickett, Christiansen, & Cottrell, 2007), such attempts typically only work on toy data or on tasks…”
Toddlers encode similarities among novel words from meaningful sentences. (2015, positive): “However, adult word knowledge includes much more than just the meanings of isolated words; the structure of our lexicalsemantic knowledge is better described as a web or network than as a dictionary (Elman, 2009; McNamara, 2005; Rogers & McClelland, 2004).”
Word learning emerges from the interaction of online referent selection and slow associative learning (2012, background): “A number of researchers argue that word learning cannot be associative: The fundamental mechanisms are social (Golinkoff & Hirsh-Pasek, 2006; Nazzi & Bertoncini, 2003), referential or conceptual (Waxman & Gelman, 2009), or constraint based (Woodward & Markman, 1998).”
Words and the World (2015, background): “A very different perspective is that language input directly affects mental states just like other perceptual inputs (Elman, 2009).”
The Symbol Grounding Problem Has Been Solved : Or Maybe Not ? (2010, background): “April 2010 IEEE CIS AMD Technical Committee 6 Since dynamics co-occur with symbols, external patterns become cues to meaning (Elman, 2009).”