@inproceedings {7362,
	title = {{\textquotedblleft}No, I AM{\textquotedblright}: What are you saying {\textquotedblleft}no{\textquotedblright} to?},
	volume = {21},
	year = {2018},
	pages = {1241{\textendash}1252},
	author = {Ye Tian and Jonathan Ginzburg}
}
@inproceedings {5823,
	title = {"No I Am": What are you saying "No" to?},
	year = {2016},
	address = {Edimbourg},
	abstract = {<p>The English particle \&ldquo;no\&rdquo; can be used in a variety of contexts. We propose that \&ldquo;no\&rdquo; is three ways ambiguous, distinguished by the type of antecedent utilized: explicit, implicit and exophoric. The second type\&mdash;\&ldquo;no\&rdquo; with an implicit antecedent addresses a grounding misalignment caused by sources such as speaker\&rsquo;s bias. This type of \&ldquo;no\&rdquo; cannot be used bare. The current semantic theories on \&ldquo;no\&rdquo; as an answer particle to negative polar questions and assertions claim that \&ldquo;no\&rdquo; is ambiguous between confirming and rejecting the polar question or assertion. The preceding negative polar question or assertion licenses and therefore provides the content for \&ldquo;no\&rdquo; in answers like \&ldquo;No, I AM\&rdquo;. We argue instead that the ambiguity arises from whether \&ldquo;no\&rdquo; is picking an an explicit antecedent\&mdash;the queried proposition\&mdash;or an implicit one\&mdash;the questioner\&rsquo;s bias. We offer three predictions and show that even positive antecedents with implied bias may license the \&ldquo;No, I AM\&rdquo; type of answer; in dialogue, bare \&ldquo;no\&rdquo;s only pick up explicit antecedents; the strength of the bias in a negative question influences the rate of the second type of \&ldquo;no\&rdquo; uses. We formalize our account in the KoS framework (Ginzburg, 2012). Our analysis highlights the importance of potential mismatches between the information states of different conversational participants in meaning resolution.</p>
},
	keywords = {dialogue, KoS, negation, No, non-sentential utterance, polarity particle},
	author = {Ye Tian and Jonathan Ginzburg}
}
