Discourse relation classification is an important component for automatic discourse parsing and natural language understanding. The performance bottleneck of a discourse parser comes from implicit discourse relations, whose discourse connectives are not overtly present. Explicit discourse connectives can potentially be exploited to collect more training data to collect more data and boost the p...

We present an approach to automatically identifying the arguments of discourse connectives based on data from the Penn Discourse Treebank. Of the two arguments of connectives, called Arg1 and Arg2, we focus on Arg1, which has proven more challenging to identify. Our approach employs a sentence-based representation of arguments, and distinguishes intra-sentential connectives, which take both the...

Arguments have always played a central role within logic and philosophy. But little attention has been paid to arguments as distinctive kind of discourse, with its own semantics pragmatics. The goal this essay is study the mechanisms by means which we make in starting from argument connectives such ‘therefore’. While some proposals made literature, they fail account for anaphoric behavior ‘ther...

Several fuzzy connectives, including those proposed by Lotfi Zadeh, can be seen as linear extensions of the Boolean connectives from the scale ${0,1}$ into the scale $[0,1]$. We discuss these extensions, in particular, we focus on the dualities arising from the Boolean dualities. These dualities allow to transfer the results from some particular class of extended Boolean functions, e.g., from c...

Estimates are given of the number B(n; L) of distinct functions computed by propositional formulas of size L in n variables, constructed using only literals and ^; _ connectives. (L is the number of occurrences of variables. L ?1 is the number of binary ^'s and _'s. B(n; L) is also the number of functions computed by two terminal series-parallel networks with L switches.) Enroute the read-once ...