How to represent meanings in an ontology

We work on a method for giving a formal semantic representation of natural language texts. The semantic representation is generated in an ontology, on the basis of morphological and syntactic information. The task of the semantic analysis is to create instances in the ontology that contains the world model, i.e. to create those individuals and relations that correspond to the situation described by the text. The knowledge base of the semantic analyser is stored in an OWL ontology. This paper gives an overview of the system, and we discuss those questions of ontology design that require special attention in the context of meaning representation. We also present a software prototype that is based on the method and generates electronic medical records from free-form medical texts

Semantic Grounding Strategies for Tagbased Recommender Systems

Recommender systems usually operate on similarities between recommended items or users. Tag based recommender systems utilize similarities on tags. The tags are however mostly free user entered phrases. Therefore, similarities computed without their semantic groundings might lead to less relevant recommendations. In this paper, we study a semantic grounding used for tag similarity calculus. We show a comprehensive analysis of semantic grounding given by 20 ontologies from different domains. The study besides other things reveals that currently available OWL ontologies are very narrow and the percentage of the similarity expansions is rather small. WordNet scores slightly better as it is broader but not much as it does not support several semantic relationships. Furthermore, the study reveals that even with such number of expansions, the recommendations change considerably.Comment: 13 pages, 5 figure

Ontology in Coq for a Guided Message Composition

International audienceNatural language generation is based on messages that represent meanings , and goals that are the usual starting points for communicate. How to help people to provide this conceptual input or, in other words, how to communicate thoughts to the computer? In order to express something, one needs to have something to express as an idea, a thought or a concept. The question is how to represent this. In 2009, Michael Zock, Paul Sabatier and Line Jakubiec-Jamet suggested the building of a resource composed of a linguistically motivated ontology, a dictionary and a graph generator. The ontology guides the user to choose among a set of concepts (or words) to build the message from; the dictionary provides knowledge of how to link the chosen elements to yield a message (compositional rules); the graph generator displays the output in visual form (message graph representing the user's input). While the goal of the ontology is to generate (or analyse) sentences and to guide message composition (what to say), the graph's function is to show at an intermediate level the result of the encoding process. The Illico system already proposes a way to help a user for generating (or analyzing) sentences and guiding their composition. Another system, the Drill Tutor, is an exercise generator whose goal is to help people to become fluent in a foreign language. It helps people (users have to make choices from the interface in order to build their messages) to produce a sentence expressing a message from an idea (or a concept) to its linguistic realization (or a correct sentence given in a foreign language). These two systems led us to consider the representation of the conceptual information into a symbolic language; this representation is encoded in a logic system in order to automatically check conceptual well-formedness of messages. This logic system is the Coq system used here only for its high level language. Coq is based on a typed λ-calculus. It is used for analysing conceptual input interpreted as types and also for specifying general definitions representing messages. These definitions are typed and they will be instanciated for type-checking the conceptual well-formedness of messages. 2 Line Jakubiec-Jame

Lexical Flexibility, Natural Language, and Ontology

The Realist that investigates questions of ontology by appeal to the quantificational structure of language assumes that the semantics for the privileged language of ontology is externalist. I argue that such a language cannot be (some variant of) a natural language, as some Realists propose. The flexibility exhibited by natural language expressions noted by Chomsky and others cannot obviously be characterized by the rigid models available to the externalist. If natural languages are hostile to externalist treatments, then the meanings of natural language expressions serve as poor guides for ontological investigation, insofar as their meanings will fail to determine the referents of their constituents. This undermines the Realist’s use of natural languages to settle disputes in metaphysics

On relating functional modeling approaches: abstracting functional models from behavioral models

This paper presents a survey of functional modeling approaches and describes a strategy to establish functional knowledge exchange between them. This survey is focused on a comparison of function meanings and representations. It is argued that functions represented as input-output flow transformations correspond to behaviors in the approaches that characterize functions as intended behaviors. Based on this result a strategy is presented to relate the different meanings of function between the approaches, establishing functional knowledge exchange between them. It is shown that this strategy is able to preserve more functional information than the functional knowledge exchange methodology of Kitamura, Mizoguchi, and co-workers. The strategy proposed here consists of two steps. In step one, operation-on-flow functions are translated into behaviors. In step two, intended behavior functions are derived from behaviors. The two-step strategy and its benefits are demonstrated by relating functional models of a power screwdriver between methodologies

Interchanging lexical resources on the Semantic Web

Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in ‘‘data silos’’ and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gap

Ontological and Epistemological Reflexivity: A Core Skill for Therapists

This paper develops the argument that a core skill needed to be an effective therapist is to have acquired an awareness of one’s own ontological and epistemological position in relation to one’s work as a therapist. In the same way that researchers need to develop reflexive awareness of their assumptions about what there is to know (ontology) and how they can come to know about it (epistemology), therapists need to be aware of their fundamental assumptions about human beings and the world they live in (ontology) as well as their beliefs about how best to develop an understanding of their clients and the meaning(s) of their experiences (epistemology). Regardless of which particular therapeutic model is adopted, the language used to talk about (and in) therapy, the kinds of questions asked of clients and the comments/interpretations offered, all presuppose and reinforce particular versions of human being and experiencing which are themselves not usually questioned or challenged during the course of therapy. In this paper it will be argued that it is essential that therapists are aware of their own fundamental assumptions about what it means to be human, and that they recognise their ontological and epistemological positions as positions that they are taking (rather than perceiving them to be self-evident truths). This is important for two reasons: i) if clients do not share the therapist’s assumptions (ie. their ‘model of the person’), the therapeutic work cannot proceed and be effective; ii) without such an awareness, therapists are at risk of unwittingly imposing their own model of the person upon the client which raises ethical issues

What Makes Logical Truths True?

The concern of deductive logic is generally viewed as the systematic recognition of logical principles, i.e., of logical truths. This paper presents and analyzes different instantiations of the three main interpretations of logical principles, viz. as ontological principles, as empirical hypotheses, and as true propositions in virtue of meanings. I argue in this paper that logical principles are true propositions in virtue of the meanings of the logical terms within a certain linguistic framework. Since these principles also regulate and control the process of deduction in inquiry, i.e., they are prescriptive for the use of language and thought in inquiry, I argue that logic may, and should, be seen as an instrument or as a way of proceeding (modus procedendi) in inquiry

Abstraction as a basis for the computational interpretation of creative cross-modal metaphor

Various approaches to computational metaphor interpretation are based on pre-existing similarities between source and target domains and/or are based on metaphors already observed to be prevalent in the language. This paper addresses similarity-creating cross-modal metaphoric expressions. It is shown how the “abstract concept as object” (or reification) metaphor plays a central role in a large class of metaphoric extensions. The described approach depends on the imposition of abstract ontological components, which represent source concepts, onto target concepts. The challenge of such a system is to represent both denotative and connotative components which are extensible, together with a framework of general domains between which such extensions can conceivably occur. An existing ontology of this kind, consistent with some mathematic concepts and widely held linguistic notions, is outlined. It is suggested that the use of such an abstract representation system is well adapted to the interpretation of both conventional and unconventional metaphor that is similarity-creating