Extending Automated Analysis of Natural Language Use Cases to Other Languages

Author(s):  
Avik Sinha ◽  
Amit Paradkar ◽  
Hironori Takeuchi ◽  
Taiga Nakamura
2002 ◽  
Vol 8 (2-3) ◽  
pp. 93-96
Author(s):  
AFZAL BALLIM ◽  
VINCENZO PALLOTTA

The automated analysis of natural language data has become a central issue in the design of intelligent information systems. Processing unconstrained natural language data is still considered as an AI-hard task. However, various analysis techniques have been proposed to address specific aspects of natural language. In particular, recent interest has been focused on providing approximate analysis techniques, assuming that when perfect analysis is not possible, partial results may be still very useful.


2021 ◽  
Vol 27 (1) ◽  
pp. 46-63
Author(s):  
Gilberto Gomes

External negation of conditionals occurs in sentences beginning with ‘It is not true that if’ or similar phrases, and it is not rare in natural language. A conditional may also be denied by another with the same antecedent and opposite consequent. Most often, when the denied conditional is implicative, the denying one is concessive, and vice versa. Here I argue that, in natural language pragmatics, ‘If $A$, $\sim B$’ entails ‘$\sim$(if $A, B$)’, but ‘$\sim$(if $A, B$)’ does not entail ‘If $A$, $\sim B$’. ‘If $A, B$’ and ‘If $A$, $\sim B$’ deny each other, but are contraries, not contradictories. Truth conditions that are relevant in human reasoning and discourse often depend not only on semantic but also on pragmatic factors. Examples are provided showing that sentences having the forms ‘$\sim$(if $A, B$)’ and ‘If $A$, $\sim B$’ may have different pragmatic truth conditions. The principle of Conditional Excluded Middle, therefore, does not apply to natural language use of conditionals. Three squares of opposition provide a representation the aforementioned relations.


2021 ◽  
Vol 3 ◽  
Author(s):  
Marieke van Erp ◽  
Christian Reynolds ◽  
Diana Maynard ◽  
Alain Starke ◽  
Rebeca Ibáñez Martín ◽  
...  

In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of recipes and food. We present the state-of-the-art and some use cases, followed by a discussion of challenges. Our perspective on addressing these is that while they typically have a technical nature, they nevertheless require an interdisciplinary approach combining natural language processing and artificial intelligence with expert domain knowledge to create practical tools and comprehensive analysis for the food domain.


2011 ◽  
Vol 20 (1) ◽  
pp. 43-58
Author(s):  
Deborah F. Rossen-Knill

This article offers an analysis of the dialogue in Julian Barnes’s Arthur & George, drawing on relevance theory (Grice, 1989; Sperber and Wilson, 1995) and politeness theory (Brown and Levinson, 1987; Fraser, 1990; Lakoff, 1973; Leech, 1983; Spencer-Oatey, 2002). The analysis demonstrates how Arthur’s and George’s particular ability to use language shapes their social situations. George’s inability to make sense of implicature and recover interpersonal messages leads to social disaster; whereas, Arthur’s heightened sensitivity to language’s creative possibilities leads to exceptional social success. The analysis has the secondary effect of revealing the intimate and indivisible relationship among natural language ability, language use, and social identity.


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