Abstract
Multilayered Extended Semantic Networks (abbreviated: MultiNet) are one of the few knowledge representation paradigms along the line of Semantic Networks (abbreviated: SN) with a comprehensive, systematic, and publicly available documentation. In contrast to logically oriented meaning representation systems with their extensional interpretation, MultiNet is based on a use-theoretic operational semantics. MultiNet is distinguished from the afore-mentioned systems by fulfilling the criteria of homogeneity and cognitive adequacy. The paper describes the main features of MultiNet and the standard repertoire of representational means provided by this system. Besides of the structural information, which is manifested in the relational and functional connections between nodes of the semantic network, the conceptual representatives of MultiNet are characterized by embedding the nodes of the network into a multidimensional space of layer attributes. To warrant cognitive adequacy and universality of the knowledge representation system, every node of the SN uniquely represents a concept, while the relations between them have to be expressed by a predefined set of about 110 semantic primitive relations and functions. The knowledge representation language MultiNet has been used as an interface in several natural language processing systems. It is also suitable as an interlingua for machine translation systems.
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References
Allgayer, J. and Reddig, C. (1990). What KL-ONE lookalikes need to cope with natural language-scope and aspect of plural noun phrases. In Sorts and Types in Artificial Intelligence (edited by Bläsius, K.; Hedstück, U.; and Rollinger, C.-R.), pp. 240–285. Berlin, Germany: Springer.
Baader, F.; Molitor, R.; and Tobies, S. (1998). On the relation between conceptual graphs and description logics. Technical Report LTCS-Report 98-11, Aachen University of Technology, Aachen, Germany.
Brachman, R. (1978). Structured inheritance networks. Technical Report No. 3742, Bolt Beranek & Newman, Cambridge, Massachusetts.
Gnörlich, C. (2000). MultiNet/WR: A Knowledge Engineering Toolkit for Natural Language Information. Technical Report 278, University Hagen, Hagen, Germany.
Helbig, H. (2001). Die semantische Struktur natürlicher Sprache: Wissensrepräsentation mit MultiNet. Berlin: Springer.
Helbig, H.; Gnörlich, C.; and Leveling, J. (2000). Natürlichsprachlicher Zugang zu Informationsanbietern im Internet und zu lokalen Datenbanken. In Sprachtechnologie für eine dynamische Wirtschaft im Medienzeitalter (edited by Schmitz, K.-D.), pp. 79–94. Wien: TermNet.
Helbig, H.; Gnörlich, C.; and Menke, D. (1996). Realization of a user-friendly access to networked information retrieval systems. Informatik-Bericht 196, FernUniversität Hagen, Hagen, Germany.
Helbig, H. and Hartrumpf, S. (1997). Word class functions for syntactic-semantic analysis. In Proceedings of the 2nd International Conference on Recent Advances in Natural Language Processing (RANLP’97), pp. 312–317. Tzigov Chark, Bulgaria.
Kamp, H. and Reyle, U. (1993). From Discourse to Logic: Introduction to Modeltheoretic Semantics of Natural Language, Formal Logic and Discourse Representation Theory. Number 42 in Studies in Linguistics and Philosophy. Dordrecht: Kluwer Academic Publishers.
Knoll, A.; Altenschmidt, C.; Biskup, J.; Blüthgen, H.-M.; Glöckner, I.; Hartrumpf, S.; Helbig, H.; Henning, C.; Karabulut, Y.; Lüling, R.; Monien, B.; Noll, T.; and Sensen, N. (1998). An integrated approach to semantic evaluation and content-based retrieval of multimedia documents. In Proceedings of the 2nd European Conference on Digital Libraries (ECDL’98) (edited by Nikolaou, C. and Stephanidis, C.), number 1513 in Lecture Notes in Computer Science, pp. 409–428. Berlin:Springer.
Peltason, C. (1991). The BACK system-An overview. SIGART Bulletin, 2(3):114–119.
Quillian, M. R. (1968). Semantic memory. In Semantic Information Processing (edited by Minsky, M.), pp. 227–270. Cambridge, Massachusetts: MIT Press.
Schulz, M. (1999). Eine Werkbank zur interaktiven Erstellung semantikbasierter Computerlexika. Ph.D. thesis, FernUniversität Hagen, Hagen, Germany.
Shapiro, S. C. (1999). SnePS: A logic for natural language understanding and commonsens reasoning. In Natural Language Processing and Knowledge Representation: Language for Knowledge und Knowledge for Language (edited by Iwanska, L. and Shapiro, S.). Cambridge, Mass.: The MIT Press.
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Helbig, H., Gnörlich, C. (2002). Multilayered Extended Semantic Networks as a Language for Meaning Representation in NLP Systems. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2002. Lecture Notes in Computer Science, vol 2276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45715-1_6
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DOI: https://doi.org/10.1007/3-540-45715-1_6
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