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Choosing the wrong word in a machine translation or natural language generation system can convey unwanted connotations, implications, or attitudes. The choice between near-synonyms such as error, m...
We compare two ways of obtaining lexical knowledge for antecedent selection in other-anaphora and definite noun phrase coreference. Specifically, we compare an algorithm that relies on links encoded i...
Given the promising title, from which one might expect a comprehensive look at imposing order on knowledge, this is a little disappointing. The back-cover blurb insists that the book can be used to pr...
For Sowa, “Knowledge representation is the application of logic and ontology to the task of constructing computable models for some domain” (p. xii). “This book is a general textbook of knowledge-base...
The strong connection between knowledge representation and reasoning and natural language is the main theme of this book. The book is divided into two parts.Part I, consisting of five original or upda...
Word sense disambiguation (WSD) is a computational linguistics task likely to benefit from the tradition of combining different knowledge sources in artificial intelligence research. An i...
In contrast, a state-of-the-art natural language generation (NLG) system would likely be able to produce only one of them, modulo variations introduced by, for example, passivization, topicalization,...
When (computational) linguists speak of “lexical semantics,” quite often they are actually referring to the more narrow area of verb semantics. Similarly, this book chooses the fairly abstract title ...
According to Bowers (2009), the finding that there are neurons with highly selective responses to familiar stimuli supports theories positing localist representations over approaches positing the type...
Putting knowledge in its place:A scheme for programming parallel processing structures on the fly.
Retrieving general and specific information from stored knowledge of specifics.
We initially describe a feature-rich discriminative Conditional Random Field (CRF) model for Information Extraction in the workshop announcements domain, which offers good baseline performance in the ...
We present a machine learning approach to robust textual inference, in which parses of the text and the hypothesis sentences are used to measure their asymmetric “similarity”, and thereby to decide if...
In this study, we used event-related potentials (ERPs) to evaluate the contribution of surface color and color knowledge information in object identification. We constructed two color-object verificat...
Source monitoring can be influenced by information that is external to the study context, such as beliefs and general knowledge (Johnson, Hashtroudi, & Lindsay, 1993). We investigated the extent to wh...

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