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Levinson's book presents a theory of generalized conversational implicature (GCI), and makes the central claim that this theory necessitates a "new view of the architecture of the theory of meaning" (p. 9). Levinson claims that to account for GCI (and other types of presumptive meanings, or preferred interpretations), it is necessary to distinguish a new(More)
We have analyzed a corpus of human-authored arguments expressed in text and information graphics, non-pictorial graphics such as bar graphs. The goal of our research is to enable intelligent argument generation systems to make effective use of these media. This paper presents and compares two classification schemes used to analyze the corpus, illustrated by(More)
This paper extends language understanding and plan inference to information graphics. We identify the kinds of communicative signals that appear in information graphics, describe how we utilize them in a Bayesian network that hypothesizes the graphic's intended message, and discuss the performance of our implemented system. This work is part of a larger(More)
This paper presents a corpus study that explores the extent to which captions contribute to recognizing the intended message of an information graphic. It then presents an implemented graphic interpretation system that takes into account a variety of communicative signals, and an evaluation study showing that evidence obtained from shallow processing of the(More)
For people who use text-based web browsers, graphs, diagrams, and pictures are inaccessible. Yet, such diagrams are quite prominent in documents commonly found on the web. In this work we describe a method for rendering important aspects of a line graph as plain text. Our method relies heavily on research in natural language generation and is motivated by(More)
We developed a Bayesian network coding scheme for annotating biomedical content in layperson-oriented clinical genetics documents. The coding scheme supports the representation of probabilistic and causal relationships among concepts in this domain, at a high enough level of abstraction to capture commonalities among genetic processes and their relationship(More)