Expressivism is most widely known as a thesis that semantically complements non-cognitivism in meta-ethics: if there are no moral facts to be known, if moral judgements or statements are not capable of being true or false, then the meaning of morally evaluative sentences cannot centrally consist in their having a truth conditional content, expressing a truth-evaluable proposition. But since the...

Preverbal focus in Hungarian has been argued to be more exhaustive or exhaustive in a distinguished way as compared to what has been generally called prosodic focus in languages like English or German. In virtually all analysis it has been assumed that the reason for this property of Hungarian focus is related to its immediately preverbal syntactic position. This effect has thus been derived co...

Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...

• A diverse captioning model of full convolution design is proposed. We develop a new evaluation metric to assess the sentence diversity. Our method achieves superior performance compared state-of-the-art benchmarks. Automatically describing video content with text description challenging but important task, which has been attracting lot attention in computer vision community. Previous works ma...

Motivated by problems that arise in computing degrees of belief, we consider the problem of computing asymptotic conditional probabilities for first-order sentences. Given firstorder sentences φ and θ, we consider the structures with domain {1, . . . , N} that satisfy θ, and compute the fraction of them in which φ is true. We then consider what happens to this fraction as N gets large. This ext...

The meaning of conditional sentences bears an intrinsic relation to a number of central philosophical problems, like the nature of reasoning, the possibility of knowledge, and the status of laws of nature. This has incited philosophers to spend a lot of time working on conditionals and to fill countless bookshelves with inspiring and sophisticated theories on their meaning. However, the overall...

Learning distributed sentence representations remains an interesting problem in the field of Natural Language Processing (NLP). We want to learn a model that approximates the conditional latent space over the representations of a logical antecedent of the given statement. In our paper, we propose an approach to generating sentences, conditioned on an input sentence and a logical inference label...

In this paper, we present a dependency treebased method for sentiment classification of Japanese and English subjective sentences using conditional random fields with hidden variables. Subjective sentences often contain words which reverse the sentiment polarities of other words. Therefore, interactions between words need to be considered in sentiment classification, which is difficult to be ha...

Abstract Relational extraction plays an important role in the field of natural language processing to predict semantic relationships between entities a sentence. Currently, most models have typically utilized tools capture high-level features with attention mechanism mitigate adverse effects noise sentences for prediction results. However, task relational classification, these mechanisms do not...

The question of conditional inference, i.e., which sentences the form ``if A then, normally, B'' should follow from a set KB such sentences, has been one classic questions AI, with several well-known solutions proposed. Perhaps most notable is rational closure construction Lehmann and Magidor, under inferred conditionals forms consequence relation, satisfies all rules preferential reasoning, *p...