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Found 14 papers, 1 papers with code
Fine-grained Entailment: Resources for Greek NLI and Precise Entailment
First, we extend the Greek version of the FraCaS test suite to include examples where the inference is directly linked to the syntactic/morphological properties of Greek.
Personae under uncertainty: The case of topoi
In this paper, we propose a probabilistic model of social signalling which adopts a persona-based account of social meaning.
Bayesian Classification and Inference in a Probabilistic Type Theory with Records
We propose a probabilistic account of semantic inference and classification formulated in terms of probabilistic type theory with records, building on Cooper et.
In Search of Meaning and Its Representations for Computational Linguistics
In this paper we examine different meaning representations that are commonly used in different natural language applications today and discuss their limits, both in terms of the aspects of the natural language meaning they are modelling and in terms of the aspects of the application for which they are used.
Dogwhistles as Inferences in Interaction
In this paper we will argue that the nature of dogwhistle communication is essentially dialogical, and that to account for dogwhistle meaning we must consider dialogical events in which dialogue partners can draw different conclusions based on communicative events.
Distributional properties of political dogwhistle representations in Swedish BERT
“Dogwhistles” are expressions intended by the speaker have two messages: a socially-unacceptable “in-group” message understood by a subset of listeners, and a benign message intended for the out-group.
We went to look for meaning and all we got were these lousy representations: aspects of meaning representation for computational semantics
In this paper we examine different meaning representations that are commonly used in different natural language applications today and discuss their limits, both in terms of the aspects of the natural language meaning they are modelling and in terms of the aspects of the application for which they are used.
Distribution is not enough: going Firther
Much work in contemporary computational semantics follows the distributional hypothesis (DH), which is understood as an approach to semantics according to which the meaning of a word is a function of its distribution over contexts which is represented as vectors (word embeddings) within a multi-dimensional semantic space.
