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References

  • Boguraev, B., Briscoe, E., Carroll, J., Carter, D., and Grover, C. (1987). The derivation of a grammatically indexed lexicon from the Longman Dictionary of Contemporary English. Proceedings of the 25th Annual Meeting of the Association for Computational Linguistics (ACL87), Stanford, CA: 193–200.

    Google Scholar 

  • Briscoe, E. and Carroll, J. (2002). Robust accurate statistical annotation of general text. Proceedings of the 3rd Int. Conference on Language Resources and Corpora (LREC02), Las Palmas, Gran Canaria: 1499–1504.

    Google Scholar 

  • Carabello, S. and Charniak, E. (1998). New figures of merit for best-first probabilistic chart parsing. Computational Linguistics 24.2: 275–298.

    Google Scholar 

  • Carroll, J. and Briscoe, E. (2002). High precision extraction of grammatical relations. Proceedings of the 19th Int. Conference on Computational Linguistics (Coling02), Taipei, Taiwan: 134–140.

    Google Scholar 

  • Charniak, E. (2000). A maximum entropy inspired parser. 1st Annual Meeting Nth. American Association for Computational Linguistics Morgan Kaufmann, San Mateo, CA: 132–139.

    Google Scholar 

  • Church, K. and Patil, R. (1982). Coping with syntactic ambiguity or how to put the block in the box on the table. Computational Linguistics 8: 139–149.

    Google Scholar 

  • Collins, M. (1999). Head-driven statistical models for natural language parsing. PhD Dissertation, Computer and Information Science, University of Pennsylvania.

    Google Scholar 

  • Copestake, A. and Lascarides, A. (1997). Integrating symbolic and statistical representations: the lexicon-pragmatics interface. Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics (ACL-EACL 97), Madrid: 136–143.

    Google Scholar 

  • Copestake, A. and Flickinger, D. (2000). An open-source grammar development environment and broad-coverage English grammar using HPSG. Proceedings of the Second conference on Language Resources and Evaluation (LREC-2000), Athens, Greece: 591–600.

    Google Scholar 

  • Copestake, A. (2002). Implementing Type Feature Structure Grammars. CSLI Publications.

    Google Scholar 

  • Copestake, A., Lambeau, F., Villavicencio, A., Bond, F., Baldwin, T., Sag, I.A., Flickinger, D. (2002). Multiword expressions: linguistic precision and reusability. Proceedings of the Third conference on Language Resources and Evaluation (LREC-2002), Las Palmas, Canary Islands: 1941–1947.

    Google Scholar 

  • Copestake, A. (2003). “Report on the design of RMRS.” Deliverable 1.1a: DeepThought — Hybrid Deep and Shallow Methods for Knowledge-Intensive Information Extraction

    Google Scholar 

  • Copestake, A., Flickinger, D., Sag, I.A. and Pollard, C. (in press). “Minimal Recursion Semantics: An Introduction.” Journal of Research in Language and Computation.

    Google Scholar 

  • Downing, P. (1977). On the Creation and Use of English Compound Nouns. Language 53(4): 810–842.

    Google Scholar 

  • Fellbaum, C. (editor) (1998). Wordnet, An Electronic Lexical Database. MIT Press.

    Google Scholar 

  • Hirst, G. (1983). Seman interpretation against ambiguity. TR-CS-83-25, Dept. of Computer Science, Brown University.

    Google Scholar 

  • Hobbs, J.R., Stickel, M., Appelt, D., and Martin, P. (1993). Interpretation as Abduction. Artificial Intelligence 63.1: 69–142.

    Article  Google Scholar 

  • Johnston, M. and Busa, F.. (1996). Qualia structure and the compositional interpretation of compounds. Proceedings of the ACL SIGLEX workshop on breadth and depth of semantic lexicons, Santa Cruz, CA.

    Google Scholar 

  • Kay, M. (1973). “The MIND system.” In Natural Language Processing, edited by R. Rustin, R.. Algorithmics Press, New York, 155–188.

    Google Scholar 

  • Lapata, M. (2002). The disambiguation of nominalisations. Computational linguistics 28:3: 357–388.

    Article  Google Scholar 

  • Lapata, M. and Lascarides, A. (2003a). Detecting novel compounds: the role of distributional evidence. Proceedings of the 10th conference of the European Chapter of the Association for Computational Linguistics (EACL-03), Budapest: 235–242.

    Google Scholar 

  • Lapata, M. and Lascarides, A. (2003b). A probabilistic account of logical metonymy. Computational Linguistics 29(2) 263–317.

    Article  Google Scholar 

  • Lauer, M. (1995). Designing Statistical Language Learners: Experiments on Compound Nouns. Ph.D. thesis, Macquarie University, Sydney.

    Google Scholar 

  • Leonard, R. (1984). The Interpretation of English Noun Sequences on the Computer. North-Holland, Amsterdam.

    Google Scholar 

  • Levi, J. (1978). The syntax and semantics of complex nominals. Academic Press, New York.

    Google Scholar 

  • Liberman, M. and Sproat, R. (1992). “The stress and structure of modified noun phrases in English.” In Lexical matters, edited by I.A. Sag and A. Szabolsci. CSLI Publications, 131–182.

    Google Scholar 

  • Marcus, M. (1980). A Theory of Syntactic recognition for Natural Language. MIT Press, Cambridge, MA.

    Google Scholar 

  • Pustejovsky, J. (1995). The Generative Lexicon. MIT Press, Cambridge, MA.

    Google Scholar 

  • Rosario, B. and Hearst, M.. (2001). Classifying the semantic relations in noun compounds via a domain-specific lexical hierarchy. Proceedings of the Empirical Methods in Natural Language Processing, Pittsburgh.

    Google Scholar 

  • Sparck Jones, K. (1983). “So what about parsing compound nouns?.” In Automatic natural language parsing, edited by K. Sparck Jones and Y. Wilks. Ellis Horwood, Chichester, England, 164–168.

    Google Scholar 

  • Tomita, M. (1987). An efficient augmented-context-free parsing algorithm. Computational Linguistics 13.1: 31–46.

    Google Scholar 

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Copestake, A., Briscoe, E. (2005). Noun Compounds Revisited. In: Tait, J.I. (eds) Charting a New Course: Natural Language Processing and Information Retrieval. The Kluwer International Series on Information Retrieval, vol 16. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3467-9_9

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  • DOI: https://doi.org/10.1007/1-4020-3467-9_9

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-3343-8

  • Online ISBN: 978-1-4020-3467-1

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