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Developing the Semantic Web via the Resolution of Meaning Ambiguities

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Software Engineering and Formal Methods. SEFM 2021 Collocated Workshops (SEFM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13230))

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Abstract

The paper presents an interdisciplinary project in cognitive linguistics, computer science, and mathematical logic, aimed at the development of a theoretical framework and correspondent logical tools for the treatment, in the Semantic Web context, of some typical linguistic phenomena in natural languages, such as lexical ambiguities and figures of speech. In particular, we focus on some specific features of metaphor that need to be addressed in order to enhance the overall quality of knowledge representation in the Semantic Web. To this extent, we briefly present PROL (Parametric Relational Ontology Language) as a novel ontological approach to the representation of the whole semantic content of n-ary relations usually expressed in natural language. Lastly, we show how specific instances of metaphorical expressions can be represented and dealt with via PROL.

Supported by Fondazione Banco di Sardegna (FdS 2019, research grant n. F72F20000420007).

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Notes

  1. 1.

    We do not consider here relations with no fixed arity, or multigrade predicates [30]. In the conceptual graph framework, this issue has been tackled through the notion of variadic conceptual graphs [23, §2.1.4]. We pointed out elsewhere that the apparent variability of the arity of some relations can be dealt with by the concept of a subrelation, which is a generalization to n-ary relations of the notion of a subproperty defined in RDFS [18, §2] Subrelations can be introduced in PROL by a straightforward extension of its vocabulary. Another issue concerns the order of relations, which is not always relevant, such as in a binary symmetric relation. In our view, any relation holds, or does not, for a fixed number of individuals in a given order, so that it does not even make sense to ask whether a relation holds for some individuals if they are not listed in some order [18, p. 709]. Thus, order is a necessary property of any relational fact, but this is not to say that order is relevant for any relation. In any case, the issue of the symmetry of a n-ary relation with respect to all, or even only some of its places, can also be treated through the concept of a subrelation.

  2. 2.

    In this paper we do not consider the use of conceptual graphs for the representation of n-ary relations [11], for this approach is not directly implementable in some RDF compatible language, even if this is a viable possibility (see [1]).

  3. 3.

    A possible extension of PROL may include a fuzzy treatment of n-ary relations in order to formally represent the use of fuzzy concepts in natural language (see [17].

  4. 4.

    Our choice of PROL, a RDF compatible ontological language, as the basis for our treatment of metaphor is motivated by the goal of contributing to the development of the Semantic Web, but at this early stage of the research project we cannot claim any superiority or advantage per se of our proposal with respect to other computational approaches to metaphor (for an overview, see [41]).

  5. 5.

    Of course, this is an extreme, idealized example. In most concrete cases (assuming a very informative knowledge base) we can conjecture that a would participate in some of the relations belonging to the semantic cloud of the concept ()is a dog, but the likelihood of any connection of an actor to the semantic cloud of ()is a dog would be very low when compared to the likelihood of any connection to the semantic cloud of ()is an actor.

  6. 6.

    In the case where “that actor is a dog” has a metaphorical meaning, we would see a node representing an individual dog which is tightly connected to the semantic cloud of dogs, but only abstractly connected to that of actors.

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Authors and Affiliations

  1. University of Cagliari, Cagliari, Italy

    Simone Pinna, Francesca Ervas & Marco Giunti

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  1. Simone Pinna
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  2. Francesca Ervas
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  3. Marco Giunti
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Correspondence to Simone Pinna .

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Editors and Affiliations

  1. Nazarbayev University, Nur-Sultan, Kazakhstan

    Antonio Cerone

  2. University of L'Aquila, L'Aquila, Italy

    Marco Autili

  3. Mälardalen University, Västerås, Sweden

    Alessio Bucaioni

  4. Aarhus University, Aarhus, Denmark

    Cláudio Gomes

  5. University of Urbino, Urbino, Italy

    Pierluigi Graziani

  6. University of Pisa, Pisa, Italy

    Maurizio Palmieri

  7. Sapienza University of Rome, Rome, Italy

    Marco Temperini

  8. Tokyo University of Agriculture and Technology, Tokyo, Japan

    Gentiane Venture

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Pinna, S., Ervas, F., Giunti, M. (2022). Developing the Semantic Web via the Resolution of Meaning Ambiguities. In: Cerone, A., et al. Software Engineering and Formal Methods. SEFM 2021 Collocated Workshops. SEFM 2021. Lecture Notes in Computer Science, vol 13230. Springer, Cham. https://doi.org/10.1007/978-3-031-12429-7_5

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