Negation and speculation expressions exist extensively in natural language. Identifying and separating them from the reliable information have important value for many natural language processing tasks, such as information extraction, sentiment analysis, and text mining. Since the release of BioScope corpus in 2008, several large-scale evaluation conferences and workshops provided platforms for scholars to collect corpora, define tasks, and perform evaluations. Negation and speculation information extraction has gradually become a hot topic in nature language processing in recent years. This survey mainly introduces the research background, task definition, and corpora for negation and speculation information extraction. In addition, this paper also reviews and analyzes the present researches, and outline its developing trends.
ZOU Bowei, ZHOU Guodong, ZHU Qiaoming.
Negation and Speculation Extraction: An Overview. Journal of Chinese Information Processing. 2015, 29(4): 16-24
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1]Hobbs J R. The Generic Information Extraction System[C]//Proceedings of the 5th conference on Message understanding. Stroudsburg, PA, USA: Association for Computational Linguistics, 1993: 87-91.
[2] Lakoff G. Linguistics and Natural Logic[J]. Journal of Synthese, 1972, 22(2): 151-271.
[3] Kim J D, Ohta T, Pyysalo S, et al. Overview of BioNLP09 Shared Task on Event Extraction[C]//Proceedings of the BioNLP2009 Workshop Companion Volume for Shared Task. Stroudsburg, PA, USA: Association for Computational Linguistics, 2009: 1-9.
[4] Farkas R, Vincze V, Mora G, et al. The CoNLL2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text[C]//Proceedings of the 14th Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 1-12.
[5] Morante R and Sporleder C. Modality and Negation: An Introduction to the Special Issue[J]. Computational Linguistics, 2012, 38(2): 223-260.
[6] Horn L R. A Natural History of Negation[M]. Chicago: Univ. of Chicago Press, 1989.
[7] Hyland K. Hedging in Scientific Research Articles[M]. Amsterdam: John Benjamins, 1998.
[8] Friedman C, Alderson P O, Austin J, et al. A General Natural-language Text Processor for Clinical Radiology[J]. Journal of the American Medical Informatics Association, 1994, 1(2):161-174.
[9] Friedman C and Hripcsak G. Natural Language Processing and its Future in Medicine[J]. Journal of Academic Medicine, 1999, 74(8):890-895.
[10] Chapman W W, Bridewell W, Hanbury P, et al. A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries[J]. Journal of Biomedical Informatics, 2001, 34(5):301-310.
[11] Vincze V, Szarvas G, Farkas R, et al. The BioScope Corpus: Biomedical Texts Annotated for Uncertainty, Negation and their Scopes[J]. Journal of BMC Bioinformatics, 2008, 9(11):S9.
[12] Turney P D. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews[C]//Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2002: 417-424.
[13] Councill I G, McDonald R, Velikovich L. Whats Great and Whats Not: Learning to Classify the Scope of Negation for Improved Sentiment Analysis[C]//Proceedings of the Workshop on Negation and Speculation in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 51-59.
[14] Li SS, Lee YM, Chen Y, et al. Sentiment Classification and Polarity Shifting[C]//Proceedings of the 23rd International Conference on Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 635-643.
[15] Averbuch M, Karson T, Ben-Ami B, et al. Context-Sensitive Medical Information Retrieval[J]. Journal of Studies in Health Technology and Informatics, 2004, 107(Pt1): 282-286.
[16] Bachenko J, Fitzpatrick E and Schonwetter M. Verification and Implementation of Language-Based Deception Indicators in Civil and Criminal Narratives[C]//Proceedings of the 22nd International Conference on Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2008: 41-48.
[17] Baker K, Bloodgood M, Dorr B J, et al. A Modality Lexicon and Its Use in Automatic Tagging[C]//Proceedings of the 7th Conference on International Language Resources and Evaluation, 2010: 1402-1407.
[18] Blanco E and Dan Moldovan. Semantic Representation of Negation Using Focus Detection[C]//Proceedings of 49th Annual Meeting of the Association for Computational Linguistics, Stroudsburg, PA, USA: Association for Computational Linguistics, 2011: 19-24.
[19] Palmer M, Gildea D, Kingsbury P. The Proposition Bank: An Annotated Corpus of Semantic Roles. Computational Linguistics[J], 2005, 31(1):71-106.
[20] Medlock B, Briscoe T. Weakly Supervised Learning for Hedge Classification in Scientific Literature[C]//Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2007: 992-999.
[21] Collier N, Park H S, Ogata N. The GENIA Project: Corpus-Based Knowledge Acquisition and Information Extraction from Genome Research Papers[C]//Proceedings of the 9th Conference on European Chapter of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 1999: 271-272.
[22] Ganter V, Strube M. Finding Hedges by Chasing Weasels: Hedge Detection Using Wikipedia Tags and Shallow Linguistic Features[C]//Proceedings of the ACL-IJCNLP 2009 Conference Short Papers. Stroudsburg, PA, USA: Association for Computational Linguistics, 2009: 173-176.
[23] Morante R, Schrauwen S, Daelemans W. Corpus-based Approaches to Processing the Scope of Negation Cues: an Evaluation of the State of the Art[C]//Proceedings of 9th International Conference on Computational Semantics. Bos J. and Pulman S. (editors), 2011: 350-354.
[24] Kilicoglu H, Bergler S. Recognizing Speculative Language in Biomedical Research Articles: A Linguistically Motivated Perspective[J]. Journal of BMC Bioinformatics, 2008, 9(11):S10.
[25] Sanchez G O, Poesio M. Negation of Protein-Protein Interactions: Analysis and Extraction. Journal of BMC Bioinformatics[J], 2007, 23(13): 424-432.
[26] Light M, Qiu XY, Srinivasan P. The Language of Bioscience: Facts, Peculations, and Statements in Between[C]//Proceedings of the HLT BioLINK2004. Stroudsburg, PA, USA: Association for Computational Linguistics, 2004: 17-24.
[27] Georgescul M. A Hedgehop over a Max-Margin Framework Using Hedge Cues[A]//Shared Task Proceedings of the 14th Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 26-31.
[28] zgür A, Radev D R. Detecting Speculations and their Scopes in Scientific Text[C]//Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2009: 1398-1407.
[29] vrelid L, Velldal E, Oepen S. Syntactic Scope Resolution in Uncertainty Analysis[C]//Proceedings of the 23rd International Conference on Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 1379-1387.
[30] Tang BZ, Wang XL, Wang X, et al. A Cascade Method for Detecting Hedges and their Scope in Natural Language Text[C]//Proceedings of the 14th Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 13-17.
[31] Verbeke M, Frasconi P, Van Asch V, et al. Kernel-based Logical and Relational Learning with kLog for Hedge Cue Detection[C]//Proceedings of the 22th Meeting of Computational Linguistics in the Netherlands. Tilburg, the Netherlands, 2011: 1-6.
[32] Frasconi P, Costa F, De Raedt L, et al. KLog-A Language for Logical and Relational Learning with Kernels[R]. http://www.dsi.unifi.it/~paolo/ps/klog.pdf. 2011.
[33] Chapman W W, Hanbury P, Cooper G F, et al. 2001. Evaluation of Negation Phrases in Narrative Clinical Reports[C]//Proceedings of the American Medical Informatics Association Symposium. Washington, DC, 2001: 105-109.
[34] Goldin I M, Chapman W W. Learning to Detect Negation with ‘Not’ in Medical Texts[C]//Workshop at the 26th ACM SIGIR Conference. 2003.
[35] Goryachev S, Sordo M, Zeng QT, et al. Implementation and Evaluation of Four Different Methods of Negation Detection[R]. Technical Report, DSG. 2006.
[36] Harkema H, Dowling J N, Thornblade T, et al. ConText: An Algorithm for Determining Negation, Experiencer, and Temporal Status From Clinical Reports[J]. Journal of Biomedical Informatics, 2009,42(5): 839-851.
[37] Huang Y, Lowe HJ. A Novel Hybrid Approach to Automated Negation Detection in Clinical Radiology Reports[J]. Journal of the American Medical Informatics Association, 2007, 14(3):304-311.
[38] Rokach L, Romano R, Maimon O. Negation Recognition in Medical Narrative Reports[J]. Information Retrieval Online, 2008, 11(6): 499-538.
[39] Apostolova E, Tomuro N, Fushman D D. Automatic Extraction of Lexico-Syntactic Patterns for Detection of Negation and Speculation Scopes[C]//Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers-Volume 2. Stroudsburg, PA, USA: Association for Computational Linguistics, 2011: 283-287.
[40] Morante R, Liekens A, Daelemans W. Learning the Scope of Negation in Biomedical Texts[C]//Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2008: 715-724.
[41] Morante R, Van Asch V, Daelemans W. Memory-Based Resolution of In-Sentence Scopes of Hedge Cues[C]//Proceedings of the 14th Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 40-47.
[42] Zhu QM, Li JH, Wang HL, et al. A Unified Framework for Scope Learning via Simplified Shallow Semantic Parsing[C]//Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 714-724.
[43] Li JH, Zhou GD, Wang HL, et al. Learning the Scope of Negation via Shallow Semantic Parsing[C]//Proceedings of the 23rd International Conference on Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2010: 671-679.
[44] Zou BW, Zhou GD, Zhu QM. Tree Kernel-based Negation and Speculation Scope Detection with Structured Syntactic Parse Features[C]//Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Seattle, Washington, USA: Association for Computational Linguistics, 2013: 968-976.
[45] Elkin PL, Brown SH, Bauer BA, et al. A Controlled Trial of Automated Classification of Negation from Clinical Notes[J]. BMC Medical Informatics and Decision Making, 2005, 5(13):13.