Denotation and connotation in the human-computer interface: The ‘Save as...’ command

This paper presents a semiotic technique as a means of exploring meaning and understanding in interface design and use. This is examined through a study of the interaction between the ‘file’ metaphor and ‘save as’ command metaphor. The behaviour of these (from a functional or computational basis) do not exactly match, or map onto, the meaning of the metaphor. We examine both the denotation of a term to the user, i.e. its literal meaning to that person, and the term’s connotations, i.e. any other meanings associated with the term. We suggest that the technique applied is useful in predicting future problems with understanding the use of metaphor at the interface and with designing appropriate signification for human-computer interaction. Variation in connotation was expected but a more fundamental difference in denotation was also uncovered. Moreover, the results clearly demonstrate that consistency in the denotation of a term is critical in achieving a good user understanding of the command

Literal Translation and the Materiality of Language: Lu Xun as a Case

With his insistence upon the literal rendering in Chinese of foreign texts, especially regarding syntax, Lu Xun’s understanding of “literal translation” strikes a rather distinct note in the modern Chinese literary scene. The intention behind this method, namely, the aim to “retain the tone of the original,” reveals a generative perception of language that takes language as not just the bearer of the already existent thought, but as the formative element of thought that has meaning in itself. This paper seeks to delineate the structural constitution of the materiality of language as grasped by Lu Xun. By comparing the notion of the “tone” to Wilhelm von Humboldt’s notion of the “inner form of language” and situating it within the genealogy of qi, as well as tracing its link with Zhang Taiyan’s idea of “zhiyan,” I will attempt to reveal the philosophical and historical basis of Lu Xun’s principle of “literal translation” and its significance for Chinese literary modernity in general

Exploring the Comprehension Process of Nonliteral Utterances and Some Implications for Automaticity

THE ISSUE of the comprehension process of Ll indirect speech acts has long been debated among philosophers, linguists, and psychologists (cf. Levinson, 1983; Bach & Hamish, 1979). Specifically, their debates have been centering on the role of literal sentence meaning in processing indirect speech acts performed in native languages: is the intended illocutionary force of the indirect speech act identified indirectly from its literal sentence meaning or directly from the locution without interpreting its literal meaning first? An attempt has also been made to explicate the role of literal meaning in comprehending idioms and metaphors in native language situations both theoretically and empirically (cf. Gibbs, 1980, 1982, 1986; Ortony et al., 1978; Swinney & Cutler, 1979; and others). Here, a question arises as to how the same issue has been treated in the area of comprehension of L2 nonliteral utterances. Are L2 learners comprehending nonliteral utterances made in their target language in the same manner as native speakers? Are L2 learners computing the literal sentence meaning in comprehending L2 nonliteral utterances? In this paper, an attempt will be made, first, to review how researchers have been dealing with the ways in which a hearer is said to arrive at his/her interlocutor's intention when the latter is making nonliteral utterances-indirect speech acts, idioms, and a metaphors-in both L1 and L2 situations. Then, in the subsequent section, I will make a further attempt to present a design for a study of comprehension process of L2 nonliteral utterances in order to deepen our understanding in this area

Minimal semantics and legal interpretation

In this paper I will tackle three issues. First, I aim to briefly outline the backbone of semantic minimalism, while focusing on the idea of ‘liberal truth conditions’ developed by Emma Borg in her book ‘Minimal Semantics’. Secondly, I will provide an account of the three principal views in legal interpretation: intentionalism, textualism and purposivism. All of them are based on a common denominator labelled by lawyers ‘literal meaning’. In the paper I suggest a novel way of viewing this common denominator as almost identical to the Borgian ‘liberal truth conditions’, at least at a conceptual level. In the third section I will focus on the conceptual similarities between the two ideas. I intend to depict that, although legal theorists do not admit it explicitly, they treat literal legal meaning as minimal propositional content that can be ascribed liberal truth conditions. There are two main objections to liberal truth conditions: their under-determinacy and unintuitive character. Both objections can be applied to ‘literal meaning’. However, the idea of liberal truth conditions gives an adequate account of what lawyers call literal meaning and is helpful in explaining the mechanism of understanding of provisions and reasons leading to the necessity of statutory interpretation

Representative Literal and Nonliteral Speech Acts in Novels “Dear Allah” by Diana Febi: A Sociopragmatic Review

This qualitative descriptive study aims to describe the representation of literal and nonliteral speech acts in the novel "Dear Allah" by Diana Febi. From a theoretical perspective, this research uses a sociopragmatic system or view. While the method or technique of data collection in this research is a documentation study or literature study, in this case, the literature review is in the form of texts contained in the novel Dear Allah by Diana Febi. The novel is the primary data source. Documentation or literature studies are carried out through direct appreciation and rational understanding of the meaning implied in the novel. The results of this study show (1) representative literal speech acts in Diana Febi's novel Dear Allah and (2) representative nonliteral speech acts in Diana Febi's novel Dear Allah. This research makes a scientific contribution, especially in linguistics, on the sociopragmatic aspect so that understanding the implied meaning of a novel can be understood as a whole in terms of social meaning

Pozadosłowne rozumienie emocji

The meaning of emotions and the meaning of words- emotions’ labels are described in studiem about emotions. Although there are some differences between these two domains, most studies about understanding emotions use lexical approach. On the other hand, the nonspecific limits inspired by language can be noticed in the area of changes in emotion meaning. Two studies were conducted and metaheuristic postulates were involved with the aim of breaking these limits. The denotation and emotional complexity were examined/analyzed in the first study. In the second study the atypical connotations taken from the psychology of creativity were used. The outcomes were discussed in relation to abstraction and metaphor as a result it is possible to go beyond literal understanding of emotions and express emotions verbally.The meaning of emotions and the meaning of words- emotions’ labels are described in studiem about emotions. Although there are some differences between these two domains, most studies about understanding emotions use lexical approach. On the other hand, the nonspecific limits inspired by language can be noticed in the area of changes in emotion meaning. Two studies were conducted and metaheuristic postulates were involved with the aim of breaking these limits. The denotation and emotional complexity were examined/analyzed in the first study. In the second study the atypical connotations taken from the psychology of creativity were used. The outcomes were discussed in relation to abstraction and metaphor as a result it is possible to go beyond literal understanding of emotions and express emotions verbally

Modeling brain activity associated with metaphor processing with distributional semantic models

In this study we investigate how lexical-semantic relations associated with the literal meaning (and abstract meaning) are being accessed across the brain during familiar metaphor comprehension. We utilize a data-driven whole-brain searchlight similarity-decoding analysis. We contrast decoding metaphoric phrases (”she’s grasping the idea”) using distributional semantic models of the verb in the phrase (VERB model) versus that of the more abstract verb-sense (PARAPHRASE VERB model) obtained from literal paraphrases of the metaphoric phrases (”she’s understanding the idea”). We showed successful decoding with the VERB model across frontal, temporal and parietal lobes mainly within areas of the language and default-mode networks. In contrast, decoding with the PARAPHRASE VERB model was restricted to frontal-temporal lobes within areas of the language-network which overlapped to some extent with significant decoding with the VERB model. Overall, the results suggest that lexical-semantic relations closely associated with the abstract meaning in metaphor processing are largely localized to language and amodal (multimodal) semantic memory systems of the brain, while those more associated with the literal meaning are processed across a distributed semantic network including areas implicated in mental imagery and social-cognitio

Systematic word meta-sense extension

The meaning of polysemous words often varies in a highly productive yet predictable way. Generalizing the regularity between conventional senses to derive novel word meaning is crucial for automated processing of non-literal language uses such as figurative expressions. We introduce a novel task called systematic word meta-sense extension (SWORME) to test and improve language models' ability to extend word meaning to denote new semantic domains (also called meta-senses) that bear regular semantic relations with existing senses. We found that language models prefer incremental lexical semantic change toward conceptually similar meta-senses such as logical metonymy, and are much worse at predicting highly non-literal meaning extensions such as metaphors. We propose a novel analogy-based method of word meaning extension, and show that it effectively improves language model systematicity in making both gradual and radical types of meta-sense extension. We further demonstrate that learning systematic meta-sense extensions benefits language models on multiple benchmarks of figurative language understanding

Knowledge-rich Image Gist Understanding Beyond Literal Meaning

We investigate the problem of understanding the message (gist) conveyed by images and their captions as found, for instance, on websites or news articles. To this end, we propose a methodology to capture the meaning of image-caption pairs on the basis of large amounts of machine-readable knowledge that has previously been shown to be highly effective for text understanding. Our method identifies the connotation of objects beyond their denotation: where most approaches to image understanding focus on the denotation of objects, i.e., their literal meaning, our work addresses the identification of connotations, i.e., iconic meanings of objects, to understand the message of images. We view image understanding as the task of representing an image-caption pair on the basis of a wide-coverage vocabulary of concepts such as the one provided by Wikipedia, and cast gist detection as a concept-ranking problem with image-caption pairs as queries. To enable a thorough investigation of the problem of gist understanding, we produce a gold standard of over 300 image-caption pairs and over 8,000 gist annotations covering a wide variety of topics at different levels of abstraction. We use this dataset to experimentally benchmark the contribution of signals from heterogeneous sources, namely image and text. The best result with a Mean Average Precision (MAP) of 0.69 indicate that by combining both dimensions we are able to better understand the meaning of our image-caption pairs than when using language or vision information alone. We test the robustness of our gist detection approach when receiving automatically generated input, i.e., using automatically generated image tags or generated captions, and prove the feasibility of an end-to-end automated process

Pragmatic enrichment in language processing and development

The goal of language comprehension for humans is not just to decode the semantic content of sentences, but rather to grasp what speakers intend to communicate. To infer speaker meaning, listeners must at minimum assess whether and how the literal meaning of an utterance addresses a question under discussion in the conversation. In cases of implicature, where the speaker intends to communicate more than just the literal meaning, listeners must access additional relevant information in order to understand the intended contribution of the utterance. I argue that the primary challenge for inferring speaker meaning is in identifying and accessing this relevant contextual information. In this dissertation, I integrate evidence from several different types of implicature to argue that both adults and children are able to execute complex pragmatic inferences relatively efficiently, but encounter some difficulty finding what is relevant in context. I argue that the variability observed in processing costs associated with adults' computation of scalar implicatures can be better understood by examining how the critical contextual information is presented in the discourse context. I show that children's oft-cited hyper-literal interpretation style is limited to scalar quantifiers. Even 3-year-olds are adept at understanding indirect requests and "parenthetical" readings of belief reports. Their ability to infer speaker meanings is limited only by their relative inexperience in conversation and lack of world knowledge