32,795 research outputs found
Connectionist natural language parsing
The key developments of two decades of connectionist parsing are reviewed. Connectionist parsers are assessed according to their ability to learn to represent syntactic structures from examples automatically, without being presented with symbolic grammar rules. This review also considers the extent to which connectionist parsers offer computational models of human sentence processing and provide plausible accounts of psycholinguistic data. In considering these issues, special attention is paid to the level of realism, the nature of the modularity, and the type of processing that is to be found in a wide range of parsers
Pluralism without Genic Causes?
Since the fundamental challenge that I laid at the doorstep of the pluralists was to defend, with nonderivative models, a strong notion of genic cause, it is fatal that Waters has failed to meet that challenge. Waters agrees with me that there is only a single cause operating in these models, but he argues for a notion of causal ‘parsing’ to sustain the viability of some form of pluralism. Waters and his colleagues have some very interesting and important ideas about the sciences, involving pluralism and parsing or partitioning causes, but they are ideas in search of an example. He thinks he has found an example in the case of hierarchical and genic selection. I think he has not
Stochastic phonological grammars and acceptability
In foundational works of generative phonology it is claimed that subjects can
reliably discriminate between possible but non-occurring words and words that
could not be English. In this paper we examine the use of a probabilistic
phonological parser for words to model experimentally-obtained judgements of
the acceptability of a set of nonsense words. We compared various methods of
scoring the goodness of the parse as a predictor of acceptability. We found
that the probability of the worst part is not the best score of acceptability,
indicating that classical generative phonology and Optimality Theory miss an
important fact, as these approaches do not recognise a mechanism by which the
frequency of well-formed parts may ameliorate the unacceptability of
low-frequency parts. We argue that probabilistic generative grammars are
demonstrably a more psychologically realistic model of phonological competence
than standard generative phonology or Optimality Theory.Comment: compressed postscript, 8 pages, 1 figur
The processing of ambiguous sentences by first and second language learners of English
This study compares the way English-speaking children and adult second language learners of English resolve relative clause attachment ambiguities in sentences such as The dean liked the secretary of the professor who was reading a letter. Two groups of advanced L2 learners of English with Greek or German as their L1 participated in a set of off-line and on-line tasks. While the participants ' disambiguation preferences were influenced by lexical-semantic properties of the preposition linking the two potential antecedent NPs (of vs. with), there was no evidence that they were applying any structure-based ambiguity resolution strategies of the type that have been claimed to influence sentence processing in monolingual adults. These findings differ markedly from those obtained from 6 to 7 yearold monolingual English children in a parallel auditory study (Felser, Marinis, & Clahsen, submitted) in that the children's attachment preferences were not affected by the type of preposition at all. We argue that whereas children primarily rely on structure-based parsing principles during processing, adult L2 learners are guided mainly by non-structural informatio
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