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Retrieving implicit positive meaning from negated statements

Published online by Cambridge University Press:  26 February 2013

EDUARDO BLANCO
Affiliation:
Human Language Technology Research Institute, The University of Texas at Dallas Richardson, TX 75080USA email: eduardo@hlt.utdallas.edu, moldovan@hlt.utdallas.edu
DAN MOLDOVAN
Affiliation:
Human Language Technology Research Institute, The University of Texas at Dallas Richardson, TX 75080USA email: eduardo@hlt.utdallas.edu, moldovan@hlt.utdallas.edu

Abstract

This paper introduces a model for capturing the meaning of negated statements by identifying the negated concepts and revealing the implicit positive meanings. A negated sentence may be represented logically in different ways depending on what is the scope and focus of negation. The novel approach introduced here identifies the focus of negation and thus eliminates erroneous interpretations. Furthermore, negation is incorporated into a framework for composing semantic relations, proposed previously, yielding a richer semantic representation of text, including hidden inferences. Annotations of negation focus were performed over PropBank, and learning features were identified. The experimental results show that the models introduced here obtain a weighted f-measure of 0.641 for predicting the focus of negation and 78 percent accuracy for incorporating negation into composition of semantic relations.

Type
Articles
Copyright
Copyright © Cambridge University Press 2013 

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References

Baker, Collin F., Fillmore, Charles J., and Lowe, John B. 1998. The Berkeley framenet project. In Proceedings of the 17th International Conference on Computational Linguistics, Montreal, Canada, pp. 86–90.Google Scholar
Blanco, E., and Moldovan, D. 2011a. A model for composing semantic relations. In Proceedings of the 9th International Conference on Computational Semantics (IWCS 2011), Oxford, UK, pp. 45–54.Google Scholar
Blanco, E., and Moldovan, D. 2011b. Semantic representation of negation using focus detection. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), Portland, OR, pp. 581–589.Google Scholar
Blanco, E., and Moldovan, D. 2011c. Unsupervised learning of semantic relation composition. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), Portland, OR, pp. 1456–1465.Google Scholar
Bos, J. 2008. Wide-coverage semantic analysis with boxer. In Bos, J., and Delmonte, R. (eds.), Semantics in Text Processing. STEP 2008 Conference Proceedings, vol. 1. Research in Computational Semantics, pp. 277–86. London: College Publications.Google Scholar
Bos, J., and Spenader, J. 2011. An annotated corpus for the analysis of VP ellipsis. Language Resources and Evaluation 45 (2): 132.CrossRefGoogle Scholar
Boucher, J., and Osgood, Charles E. 1969, February. The pollyanna hypothesis. Journal of Verbal Learning and Verbal Behavior, 8 (1): 18.Google Scholar
Carreras, X., and Màrquez, L. 2004, May. Introduction to the CoNLL-2004 shared task: semantic role labeling. In Ng, Hwee T., and Riloff, E. (eds.), HLT-NAACL 2004 Workshop: Eighth Conference on Computational Natural Language Learning (CoNLL-2004), Boston, MA, pp. 8997. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Carreras, X., and Màrquez, L. 2005. Introduction to the CoNLL-2005 shared task: semantic role labeling. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CONLL '05), Morristown, NJ, pp. 152–64. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Choi, Jinho D., Bonial, C., and Palmer, M. 2010. Propbank instance annotation guidelines using a dedicated editor, Jubilee. In Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC’10), Valletta, Malta, pp. 18711875.Google Scholar
Cohen, Paul R., and Loiselle, Cynthia L. 1988. Beyond ISA: structures for plausible inference in semantic networks. In Proceedings of the Seventh National Conference on Artificial Intelligence, St. Paul, MN, pp. 415420.Google Scholar
Councill, I., McDonald, R., and Velikovich, L. 2010, July. What's great and what's not: learning to classify the scope of negation for improved sentiment analysis. In Proceedings of the Workshop on Negation and Speculation in Natural Language Processing, Uppsala, Sweden, pp. 51–9. Antwerp, Belgium: University of Antwerp.Google Scholar
Dang, Hoa T., and Palmer, M. 2005, June. The role of semantic roles in disambiguating verb senses. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05), Ann Arbor, MI, pp. 42–9. Stroudsburg, PA, USA: Association for Computational Linguistics.Google Scholar
Dowty, D. 1994. The role of negative polarity and concord marking in natural language reasoning. In Proceedings of Semantics and Linguistics Theory (SALT) 4, Rochester, NY, pp. 114–44.Google Scholar
Farkas, R., Vincze, V., Móra, G., Csirik, J., and Szarvas, G. 2010, July. The CoNLL-2010 shared task: learning to detect hedges and their scope in Natural Language text. In Proceedings of the Fourteenth Conference on Computational Natural Language Learning, Uppsala, Sweden, pp. 112. Stroudsburg, PA, USA: Association for Computational Linguistics.Google Scholar
Fillmore, C. J. 1976, October. Frame semantics and the nature of language. Annals of the New York Academy of Sciences (Origins and Evolution of Language and Speech), 280: 2032.Google Scholar
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., and Witten, Ian H. 2009, November. The weka data mining software: an update. SIGKDD Exploration Newsletter, 11 (1): 10–18.Google Scholar
Hendrickx, I., Kim, Su N., Kozareva, Z., Nakov, P., O'Seaghdha, D., Padó, S., Pennacchiotti, M., Romano, L., and Szpakowicz, S. 2009, June. SemEval-2010 task 8: multi-way classification of semantic relations between pairs of nominals. In Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions (SEW-2009), Boulder, Colorado, pp. 94–9. Stroudsburg, PA: Association for Computational Linguistics.CrossRefGoogle Scholar
Hintikka, J. 2002. Negation in logic and in natural language. Linguistics and Philosophy, 25 (5/6): 585600.Google Scholar
Horn, Laurence R. 1989, June. A Natural History of Negation. Chicago, IL: University of Chicago Press.Google Scholar
Horn, Laurence R., and Kato, Y. (eds.) 2000, October. Negation and Polarity – Syntactic and Semantic Perspectives (Oxford Linguistics), New York: Oxford University Press.Google Scholar
Hu, M., and Liu, B. 2004. Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '04), New York, NY, pp. 168–77. New York, NY: ACM.Google Scholar
Huddleston, Rodney D., and Pullum, Geoffrey K. 2002, April. The Cambridge Grammar of the English Language. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Huhns, Michael N., and Stephens, Larry M. 1989. Plausible inferencing using extended composition. In Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI’89), San Francisco, CA, pp. 1420–5. Burlington, MA: Morgan Kaufmann.Google Scholar
Jackendoff, R. 1972. Semantic Interpretation in Generative Grammar. Cambridge, MA: MIT Press.Google Scholar
Jia, L., Yu, C., and Meng, W. 2009. The effect of negation on sentiment analysis and retrieval effectiveness. In Proceedings of the 18th ACM Conference on Information and Knowledge Management, (CIKM '09), New York, NY, pp. 1827–30. New York, NY: ACM.Google Scholar
Kingsbury, P., Palmer, M., and Marcus, M. 2002. Adding semantic annotation to the Penn TreeBank. In Proceedings of the Human Language Technology Conference, San Diego, CA.Google Scholar
Koomen, P., Punyakanok, V., Roth, D. and Yih, Wen T. 2005, June. Generalized inference with multiple semantic role labeling systems. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005), Ann Arbor, MI, pp. 181–4. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Ladusaw, William A. 1996. Negation and polarity items. In Lappin, S. (ed.), Handbook of Contemporary Semantic Theory, pp. 321–41. Malden MA: Blackwell.Google Scholar
Lang, J., and Lapata, M. 2010, June. Unsupervised induction of semantic roles. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Los Angeles, CA, pp. 939–47. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Li, J., Zhou, G., Wang, H., and Zhu, Q. 2010, August. Learning the scope of negation via shallow semantic parsing. In Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), Beijing, China, pp. 671–9. Stroudsburg, PA: ACL (Coling 2010 Organizing Committee).Google Scholar
Löbner, S. 2000, June. Polarity in natural language: predication, quantification and negation in particular and characterizing sentences. Linguistics and Philosophy, 23 (3): 213308.Google Scholar
Marcus, M., Santorini, B. and Marcinkiewicz, Mary A. 1994. Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, 19 (2): 313–30.Google Scholar
Màrquez, L., Carreras, X., Litkowski, Kenneth C., and Stevenson, S. 2008, June. Semantic role labeling: an introduction to the special issue. Computational Linguistics, 34 (2): 145–59.Google Scholar
Merlo, P. and Van der Plas, L. 2009, August. Abstraction and generalisation in semantic role labels: PropBank, VerbNet or both? In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Suntec, Singapore, pp. 288–96. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Meyers, A., Reeves, R., Macleod, C., Szekely, R., Zielinska, V., Young, B., and Grishman, R. 2004. Annotating noun argument structure for NomBank. In Proceedings of LREC-2004, Lisbon, Portugal, pp. 803806.Google Scholar
Morante, R. 2010, May. Descriptive analysis of negation cues in biomedical texts. In Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC’10), Valletta, Malta. Paris, France: European Language Resources Association (ELRA), pp. 14291436.Google Scholar
Morante, R., and Blanco, E. 2012. *SEM 2012 shared task: resolving the scope and focus of negation. In Proceedings of *SEM 2012: The First Joint Conference on Lexical and Computational Semantics, Montréal, Canada, 7–8 June, pp. 265–74. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Morante, R., Liekens, A., and Daelemans, W. 2008, October. Learning the scope of negation in biomedical texts. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, Honolulu, Hawaii, pp. 715–24. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Morante, R., Schrauwen, S., and Daelemans, W. 2011. Corpus-based approaches to processing the scope of negation cues: an evaluation of the state of the art. In Proceedings of the 9th International Conference on Computational Semantics (IWCS 2011), Oxford, UK, pp. 350–354.Google Scholar
Morante, R., and Sporleder, C. (eds.) 2010, July. Proceedings of the Workshop on Negation and Speculation in Natural Language Processing. Antwerp, Belgium: University of Antwerp.Google Scholar
Nielsen, Leif A. 2004. Verb phrase ellipsis detection using automatically parsed text. In Proceedings of the 20th International Conference on Computational Linguistics (COLING '04), Stroudsburg, PA, Stroudsburg, PA: Association for Computational Linguistics, pp. 10931099.Google Scholar
Øvrelid, L., Velldal, E., and Oepen, S. 2010, August. Syntactic scope resolution in uncertainty analysis. In Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), Beijing, China, pp. 1379–87. Stroudsburg, PA: ACL (Coling 2010 Organizing Committee).Google Scholar
Özgür, A. and Radev, Dragomir R. 2009, August. Detecting speculations and their scopes in scientific text. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Singapore, pp. 1398–407. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Palmer, M., Gildea, D., and Kingsbury, P. 2005. The proposition bank: an annotated corpus of semantic roles. Computational Linguistics, 31 (1): 71106.Google Scholar
Pang, B., Lee, L., and Vaithyanathan, S. 2002, July. Thumbs up? sentiment classification using machine learning techniques. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing, pp. 7986. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Quirk, R., Greenbaum, S., Leech, G., and Svartvik, J. 1985. A Comprehensive Grammar of the English Language. Harlow, UK: Longman.Google Scholar
Rooth, M. 1985. Association with Focus, PhD thesis, Univeristy of Massachusetts, Amherst.Google Scholar
Rooth, M. 1992. A theory of focus interpretation. Natural Language Semantics, 1: 75116.Google Scholar
Rose, Carolyn P., Roque, A., Bhembe, D., and Vanlehn, K. 2003. A hybrid text classification approach for analysis of student essays. In Building Educational Applications Using Natural Language Processing, Stroudsburg, PA: Association for Computational Linguistics, pp. 6875.Google Scholar
Sánchez Valencia, V. 1991. Studies on Natural Logic and Categorial Grammar, PhD thesis, University of Amsterdam, Netherlands.Google Scholar
Sandu, G. 1994. Some aspects of negation in English. Synthese, 99: 345–60.Google Scholar
Saurf, R., and Pustejovsky, J. 2007. Determining modality and factuality for text entailment. In Proceedings of the International Conference on Semantic Computing, (ICSC '07), Washington, DC, pp. 509–16. Washington, DC: IEEE Computer Society.Google Scholar
Saurí, R., and Pustejovsky, J. 2008. From structure to interpretation: a double-layered annotation for event factuality. In Proceedings of the 2nd Linguistic Annotation Workshop (The LAW II), LREC 2008, Marrakech, Morocco, pp. 18.Google Scholar
Saurí, R., and Pustejovsky, J. 2009, September. FactBank: a corpus annotated with event factuality. Language Resources and Evaluation, 43 (3): 227–68.Google Scholar
Szarvas, G., Vincze, V., Farkas, R., and Csirik, J. 2008, June. The bioscope corpus: annotation for negation, uncertainty and their scope in biomedical texts. In Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, Columbus, OH, pp. 3845. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
van Munster, E. 1988. The treatment of scope and negation in Rosetta. In Proceedings of the 12th International Conference on Computational Linguistics, Budapest, Hungary, pp. 442–447.Google Scholar
Wiegand, M., Balahur, A., Roth, B., Klakow, D., and Montoyo, A. 2010, July. A survey on the role of negation in sentiment analysis. In Proceedings of the Workshop on Negation and Speculation in Natural Language Processing, Uppsala, Sweden, pp. 60–8. Antwerp, Belgium: University of Antwerp.Google Scholar
Winston, Morton E., Chaffin, R., and Herrmann, D. 1987. A taxonomy of part-whole relations. Cognitive Science, 11 (4): 417–44.Google Scholar
Zapirain, Be N., Agirre, E., and Màrquez, L. 2008, June. Robustness and generalization of role sets: PropBank vs. VerbNet. In Proceedings of ACL-08: HLT, Columbus, OH, pp. 550558. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Zeijlstra, H. 2007. Negation in natural language: on the form and meaning of negative elements. Language and Linguistics Compass, 1 (5): 498518.Google Scholar