Non-Local Contexts Help Resolve Ambiguity
Citation:
Krugman, Daniel and Vogel, Carl, Non-Local Contexts Help Resolve Ambiguity, International Conference on Artificial Intelligence, Nevada, USA, June 26-29, 2006, Castillo, Oscar [...et al.], 2006, 738-747Download Item:
Abstract:
This paper addresses nonlocal context effects in the
interpretation of ambiguous utterances in natural language.
We examine equivocation as a form of discourse
ambiguity and demonstrate that nonlocal contexts can
resolve ambiguity by providing a method for exploring
the effects of global context. Of particular relevance is
that the locus of ambiguity within the texts analyzed
is within and across quotations included in larger texts
that are representative of summaries of speeches as
reported in newspapers. This research has relevance
to sentiment analysis through the ramifications that
sentiment relevant to financial markets cannot necessarily
be detected from quoted texts alone, even when
the text quoted in the article is that of the Federal Reserve
Board chair. We think it safe to say that most
research on sentiment analysis does not distinguish between
direct text and text present indirectly via quotation.
The texts we use as experimental items in
our study involve a mixture of quoted and nonquoted
statements of Alan Greenspan, texts which are relevant
to domain-specific decision making. The results
we report suggest that sentiment analysis research is
mistaken if it does not parse for qutoational contexts
of sentiment bearing words. Our results show that
nonlocal contexts strongly influence decision making
behavior in response to ambiguous texts.
Author's Homepage:
http://people.tcd.ie/vogelDescription:
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Author: VOGEL, CARL; Krugman, Daniel
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