Abstract
This paper provides a deduction-based approach for automatically classifying compound-internal relations in GermaNet, the German version of the Princeton WordNet for English. More specifically, meronymic relations between simplex and compound nouns provide the necessary input to the deduction patterns that involve different types of compound-internal relations. The scope of these deductions extends to all four meronymic relations modeled in version 6.0 of GermaNet: component, member, substance, and portion. This deduction-based approach provides an effective method for automatically enriching the set of semantic relations included in GermaNet.
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Notes
In this paper, the term part–whole relation is sometimes abbreviated as PWR and the term meronymy/holonymy is often used synonymously.
As a matter of fact, only one of these relations is manually encoded since the inverse relation can be automatically inferred.
Component meronymy as the default class contains very heterogeneous examples. This influences the compound-internal relation “<head> has <modifier>” in the way that its interpretation covers a very broad spectrum.
We would like to thank an anonymous reviewer of an earlier version of this paper for this suggestion.
These figures are as of GermaNet release 6.0, April 2011.
Other examples of this kind are Nusskuchen ‘nut cake’, Hefeteig ‘yeast dough’, and Wasserbett ‘water bed’.
Other examples of this kind are Brustkorb ‘ribcage’, Kehlkopf ‘larynx’, Glühfadenlampe ‘incandescent lamp’, and Schienbein ‘shin’.
References
Baayen, R. H., Kuperman, V., & Bertram, R. (2010). Frequency effects in compound processing. In S. Scalise & I. Vogel (Eds.), Compounding (pp. 257–270). Amsterdam/ Philadelphia: Benjamins.
Barker, K., & Szpakowicz, S. (1998). Semi-automatic recognition of noun modifier relationships. In Proceedings of the 17th international conference on computational linguistics (COLING 1998) (pp. 96–102).
Baroni, M., Matiasek, J., & Trost, H. (2002). Predicting the components of German nominal compounds. In F. van Harmelen (Ed.), Proceedings of the 15th European conference on artificial intelligence (ECAI) (pp. 470–474). Amsterdam: IOS Press.
Cruse, D. A. (1986). Lexical semantics. Cambridge, England: Cambridge University Press.
Cruse, A. (2011). Meaning in language—an introduction to semantics and pragmatics (3rd edn.). Oxford: Oxford University Press.
Downing, P. (1977). On the creation and use of english compound nouns, language. Linguistic Society of America, 53(4), 810–842.
Eisenberg, P. (2006). Das Wort—Grundriss der deutschen Grammatik (3rd edn.). Verlag J. B. Melzer, Stuttgart/Weimar, Germany.
Fellbaum, C. (Ed.) (1998). WordNet—an electronic Lexical Database. Cambridge, Mass: The MIT Press.
Finin, T. (1980). The semantic interpretation of compound nominals, PhD Thesis, Co-ordinated Science Laboratory, University of Illinois, Urbana-Champaign.
Girju, R., Moldovan, D., Tatu, M., & Antohe, D. (2005). On the semantics of noun compounds. Journal of Computer Speech and Language—Special Issue on Multiword Expressions. A. Villavicencio, F. Bond, & D. McCarthy (Eds.), 19(4), 479–496.
Girju, R., Badulescu, A.., & Moldovan, D. (2006). Automatic discovery of part–whole relations. Computational Linguistics, 32(1), 83–135.
Henrich, V., & Hinrichs, E. (2010). GernEdiT—the GermaNet editing tool. In Proceedings of the seventh conference on international language resources and evaluation (LREC 2010) (pp. 2228–2235). Valletta, Malta.
Henrich, V., & Hinrichs, E. (2011). Determining immediate constituents of compounds in GermaNet. In Proceedings of recent advances in natural language processing (RANLP 2011) (pp. 420–426). Hissar, Bulgaria.
Hentschel, E., & Weydt, H. (2003). Handbuch der deutschen Grammatik. Berlin, Germany: Walter de Gruyter.
Heringer, H.-J. (1984). Wortbildung: Sinn aus dem Chaos. Deutsche Sprache 12, 1–13.
Jespersen, O. (1922). Language, its nature, development and origin. London: George Allen & Unwin Ltd.
Kim, S. N., & Baldwin, T. (2005). Automatic interpretation of noun compounds using WordNet similarity. In Proceedings of the 2nd international joint conference on natural language processing (pp. 945–956).
Kunze, C., & Lemnitzer, L. (2002). GermaNet—representation, visualization, application. In Proceedings of LREC 2002, main conference, Vol V. (pp. 1485–1491).
Lapata, M. (2002). The disambiguation of nominalizations. Computational Linguistics, 28(3), 357–388
Lapata, M., & Keller, F. (2004). The Web as a baseline: Evaluating the performance of unsupervised Web-based models for a range of NLP tasks. In Proceedings of the human language technology conference of the North American chapter of the Association for Computational Linguistics (pp. 121–128). Boston.
Lapata, M., & Keller, F. (2005). Web-based models for natural language processing. ACM Transactions on Speech and Language Processing, 2, 1–31
Lauer, M. (1995a). Corpus statistics meet the noun compound: Some empirical results. In Proceedings of the 33rd annual meeting of the Association for Computational Linguistics (ACL ’95) (pp. 47–54). PA, USA: Stroudsburg.
Lauer, M. (1995b). Designing statistical language learners: Experiments on compound nouns, PhD thesis, Macquarie University.
Leonard, R. (1984). The interpretation of english noun sequences on the computer. North-Holland, Amsterdam.
Levi, J. N. (1978). The syntax and semantics of complex nominals. New York: Academic Press.
Lyons, J. (1977). Semantics. London, England: Cambridge University Press.
McDonald, D. B. (1982). Understanding noun compounds, PhD Thesis. Pittsburgh, PA: Carnegie-Mellon University.
Moldovan, D., Badulescu, A., Tatu, M., Antohe, D., & Girju, R. (2004). Models for the semantic classification of noun phrases. In Proceedings of computational lexical semantics workshop at HLT- NAACL 2004 (pp. 60–67). Boston, MA.
Nastase, V., & Szpakowicz, S. (2003). Exploring noun-modifier semantic relations. In Fifth international workshop on computational semantics (IWCS-5) (pp. 285–301). Tilburg, The Netherlands.
Rosario, B., & Hearst, M. (2001). Classifying the semantic relations in noun-compounds via domain-specific lexical hierarchy. In Proceedings on 2001 conference on empirical methods in natural language processing (EMNLP-01) (pp. 82–90).
Rosario, B., Hearst, M., & Fillmore, C. (2002). The descent of hierarchy, and selection in relational semantics. In Proceedings on 40th annual meeting of the Association for Computational Linguistics (ACL-02) (pp. 417–424). Philadelphia, PA.
Stephens, M., Palakal, M. J., Mukhopadhyay, S., & Raje, R. (2001). Detecting gene relations from MEDLINE abstracts. In Proceedings on sixth annual Pacific symposium on biocomputing (pp. 483–496).
Taylor, J. R. (1989). Linguistic categorization: Prototypes in linguistic theory. Clarendon Press, Oxford
Vanderwende, L. (1993). SENS: The system for evaluating noun sequences. In K. Jensen, G. E. Heidorn & S. D. Richardson (Eds.), Natural language processing: The PLNLP approach (pp. 161–73). New York: Kluwer Academic Publishers.
Winston, M., Chaffin, R., & Herrmann, D. (1987). A taxonomy of part–whole relations. Cognitive Science, 11(4), 417–444.
Acknowledgments
We are very grateful to our research assistant Sarah Schulz, who helped us substantially revise the part–whole relations for GermaNet release 6.0. We would like to thank our colleague Christina Hoppermann and three anonymous reviewers for their extremely helpful comments on earlier versions of this paper. Special thanks go to Harald Baayen for stimulating discussions and valuable input on future directions for research. Financial support for the first and second author was provided by the German Research Foundation (DFG) as part of the Collaborative Research Center ‘Emergence of Meaning’ (SFB 833) and by the German Ministry of Education and Technology (BMBF) as part of the research grant CLARIN-D. Additional support for the third author was provided by the German Research Foundation as part of the joint research grant ‘Semantic Information Retrieval (SIR-III)’ of the Universities of Darmstadt and Tübingen.
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Appendix
Appendix
The newly modeled conceptual part–whole relations involving compounds in GermaNet allow for the deduction of 11 different compound-internal semantic relations. These deductions are summarized in Table 9.
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Hinrichs, E., Henrich, V. & Barkey, R. Using part–whole relations for automatic deduction of compound-internal relations in GermaNet. Lang Resources & Evaluation 47, 839–858 (2013). https://doi.org/10.1007/s10579-012-9207-y
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DOI: https://doi.org/10.1007/s10579-012-9207-y