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Regular polysemes are sets of ambiguous words that all share the same relationship between their meanings, such as CHICKEN and LOBSTER both referring to an animal or its meat. To probe how a distributional semantic model, here exemplified by bidirectional encoder representations from transformers (BERT), represents regular polysemy, we analyzed whether its embeddings support answering sense analogy questions similar to "is the mapping between CHICKEN (as an animal) and CHICKEN (as a meat) similar to that which maps between LOBSTER (as an animal) to LOBSTER (as a meat)?" We did so using the LRcos model, which combines a logistic regression classifier of different categories (e.g., animal vs. meat) with a measure of cosine similarity. We found that (a) the model was sensitive to the shared structure within a given regular relationship; (b) the shared structure varies across different regular relationships (e.g., animal/meat vs. location/organization), potentially reflective of a "regularity continuum;" (c) some high-order latent structure is shared across different regular relationships, suggestive of a similar latent structure across different types of relationships; and (d) there is a lack of evidence for the aforementioned effects being explained by meaning overlap. Lastly, we found that both components of the LRcos model made important contributions to accurate responding and that a variation of this method could yield an accuracy boost of 10% in answering sense analogy questions. These findings enrich previous theoretical work on regular polysemy with a computationally explicit theory and methods, and provide evidence for an important organizational principle for the mental lexicon and the broader conceptual knowledge system., (© 2024 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Lexical ambiguity is pervasive in language, and the nature of the representations of an ambiguous word's multiple meanings is yet to be fully understood. With a special focus on Chinese characters, the present study first established that native speaker's perception about a character's number of meanings was heavily influenced by the availability of its distinct word formations, while whether these meanings would be perceived to be closely related was driven by further conceptual analysis. These notions were operationalized as two computed metrics, which assessed the degree of dispersion across individual word formations and the degree of propinquity across clusters of word formations, respectively, in a distributional semantic space. The observed correlations between the computed and the perceived metrics indicated that the utility of word formations to tap into meaning representations of Chinese characters was indeed cognitively plausible. The results have demonstrated the extent to which distributional semantics could inform about meaning representations of Chinese characters, which has theoretical implications for the representation of ambiguous words more generally., (© 2023 Cognitive Science Society LLC.)

In her engaging book, The referential mechanism of proper names, Li presents empirical studies involving American and Chinese laypeople. Li interprets her results as supporting an epistemic‐perspective reading of the variability in referential intuitions on proper names. Building upon this thesis, Li defends the ambiguity view, claiming that names are ambiguous between a descriptivist and a causal‐historical meaning. I argue that either Li's data do not enable a comparison of the two theories of reference, or support for the ambiguity view is limited to the Chinese sample at most and does not rely upon the inference that Li employs. [ABSTRACT FROM AUTHOR]

Aim: We aimed to apply ontological techniques to address semantic ambiguities in protected area and conservation informatics. By doing so, we aimed to create a coherent, machine‐actionable semantic representation of the biogeographic areas (which often overlap protected areas) to support more efficient and standardized informatics, supporting research and decision‐making. We present BIOREALM, the first informatic ontology for comparative biogeography. Location: Global. Taxon: Any taxon can be integrated in BIOREALM. Methods: We convert a cladogram of biogeographic areas—generated by a process known as bioregionalization—into a series of ontological classes. Areas of endemism are treated as formal objects related by hierarchical relationships and constrained by a condition of monophyly. We use semantic web approaches to extend the Environment Ontology (ENVO) with classes for (often semantically confounded) biogeographic entities, including biogeographic areas, areas of endemism and endemic areas. We applied this approach to a bioregionalization of Australia as a case study. In all, 20 subregions which are part of the Austral Bioregionalisation Atlas have been selected for the study and integrated in BIOREALM. Results: We have created an ontology—formatted in the Web Ontology Language and adhering to the practices of the Open Biomedical and Biological Ontology Foundry—which provides a rigorous, extensible and machine‐actionable framework that can improve biogeographic analyses and interoperability between systems. One main class and 20 individuals per class were implemented. Main Conclusions: BIOREALM encodes a model‐theoretic view of endemism using semantic web approaches, offering new avenues to express and analyse biogeographic units. This approach offers a means to identify monophyletic biogeographic areas for conservation, based on specific combinations of monophyletic endemic taxa. Such an ontology provides knowledge representation solutions which supports interoperability along the FAIR (Findable, Accessible, Interoperable, Reusable) principles, thus fostering more consistent ecological informatics. [ABSTRACT FROM AUTHOR]

Recent experimental studies have claimed to find evidence for the view that natural kind terms such as "water" are ambiguous: that they have two extensions, one determined by superficial properties, the other by underlying essence. In an online experiment, we presented to 600 participants scenarios describing discoveries of novel samples that differ in deep structure from samples of a familiar kind but are superficially identical, such as a water‐like substance that is not composed of H2O. We used three different types of question sets to probe whether the participants considered the sample as a member of the kind or not. Our results did not confirm the predictions of the ambiguity view. They were, rather, consistent with views that take underlying essences to be the sole criterion for membership in a natural kind. [ABSTRACT FROM AUTHOR]

In this paper I offer a new characterisation of what makes a dispute merely verbal. This new characterisation builds on the framework initially outlined by Jenkins and additionally makes use of Stalnaker's notion of 'common ground'. I argue that this 'common ground account' can better classify disputes as merely verbal, and can better explain cases of playing devil's advocate. [ABSTRACT FROM AUTHOR]

After some generalities about connections between functions and relations in Sections 1 and 2 recalls the possibility of taking the semantic values of n‐ary Boolean connectives as n‐ary relations among truth‐values rather than as n‐ary truth functions. Section 3, the bulk of the paper, looks at correlates of these truth‐value relations as applied to formulas, and explores in a preliminary way how their properties are related to the properties of "logical relations" among formulas such as equivalence, implication (entailment) and contrariety (logical incompatibility), concentrating for illustrative purposes on binary logical relations such as those just listed. To avoid an excess of footnotes, some points have been deferred to an Appendix as "Longer Notes". [ABSTRACT FROM AUTHOR]

In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used. The ability to determine the ambiguous word's correct meaning is a Know‐distill challenging task in natural language processing (NLP). Word sense disambiguation (WSD) is an NLP process to analyze and determine the correct meaning of polysemous words in a text. WSD is a computational linguistics task that automatically identifies the polysemous word's set of senses. Based on the context some word comes into view, WSD recognizes and tags the word to its correct priori known meaning. Semitic languages like Arabic have even more significant challenges than other languages since Arabic lacks diacritics, standardization, and a massive shortage of available resources. Recently, many approaches and techniques have been suggested to solve word ambiguity dilemmas in many different ways and several languages. In this review paper, an extensive survey of research works is presented, seeking to solve Arabic word sense disambiguation with the existing AWSD datasets. This article is categorized under:Algorithmic Development > Text MiningTechnologies > Machine Learning [ABSTRACT FROM AUTHOR]

Summary: In order to improve the assemblability and reduce the cost of the parts, the material requirements can be applied to the toleranced feature and the datum feature of the coaxiality at the same time in the practical application. How to realize the information exchange between different heterogeneous systems and how to read and explain the semantics of this complex tolerance specification automatically is one of the urgent problems to be solved in intelligent digital manufacturing. Ontology described in OWL2 DL and SWRL language has strict mathematical basis of description logic, and the knowledge represented by it has clear semantics and can be read and understood directly by computer. In addition, because of its consistency checking, knowledge reasoning, and flexible query ability, it becomes the most potential knowledge representation technology in the future. On the other hand, the semantic interpretation of tolerance specification by the new generation GPS theory based on skin model has the advantages of clear semantics, no ambiguity, and consistency at different stages of the product life cycle. In this article, the enhanced semantic representation ontology for this kind of coaxiality tolerance specification is constructed based on the advantages of the new GPS theory and ontology technology and the effectiveness of the method is verified and analyzed through a case. [ABSTRACT FROM AUTHOR]