Modality and Negation: An Introduction to the Special Issue

Traditionally, most research in NLP has focused on propositional aspects of meaning. To truly understand language, however, extra-propositional aspects are equally important. Modality and negation typically contribute significantly to these extra-propositional meaning aspects. Although modality and negation have often been neglected by mainstream computational linguistics, interest has grown in recent years, as evidenced by several annotation projects dedicated to these phenomena. Researchers have started to work on modeling factuality, belief and certainty, detecting speculative sentences and hedging, identifying contradictions, and determining the scope of expressions of modality and negation. In this article, we will provide an overview of how modality and negation have been modeled in computational linguistics.

[1]  Noriko Kando,et al.  Certainty Identification in Texts: Categorization Model and Manual Tagging Results , 2023 .

[2]  Oren Etzioni,et al.  Extracting Product Features and Opinions from Reviews , 2005, HLT.

[3]  Soo-Min Kim,et al.  Determining the Sentiment of Opinions , 2004, COLING.

[4]  C. Habel,et al.  Language , 1931, NeuroImage.

[5]  Claire Cardie,et al.  Hierarchical Sequential Learning for Extracting Opinions and Their Attributes , 2010, ACL.

[6]  Lior Rokach,et al.  Context-Sensitive Medical Information Retrieval , 2004, MedInfo.

[7]  Hagit Shatkay,et al.  Multi-dimensional classification of biomedical text: Toward automated, practical provision of high-utility text to diverse users , 2008, Bioinform..

[8]  Simone Paolo Ponzetto,et al.  Collaboratively built semi-structured content and Artificial Intelligence: The story so far , 2013, Artif. Intell..

[9]  Roser Morante,et al.  A Metalearning Approach to Processing the Scope of Negation , 2009, CoNLL.

[10]  Isaac G. Councill,et al.  What's great and what's not: learning to classify the scope of negation for improved sentiment analysis , 2010, NeSp-NLP@ACL.

[11]  Roser Morante,et al.  Memory-Based Resolution of In-Sentence Scopes of Hedge Cues , 2010, CoNLL Shared Task.

[12]  D. Westerståhl The traditional square of opposition and generalized quantifiers ∗ , 2008 .

[13]  Janyce Wiebe,et al.  Tracking Point of View in Narrative , 1994, Comput. Linguistics.

[14]  Halil Kilicoglu,et al.  Recognizing speculative language in biomedical research articles: a linguistically motivated perspective , 2008, BMC Bioinformatics.

[15]  E. H. Hutten,et al.  SEMANTICS , 1953, The British Journal for the Philosophy of Science.

[16]  James Pustejovsky,et al.  Annotating and Recognizing Event Modality in Text , 2006, FLAIRS.

[17]  George Lakoff,et al.  Hedges: A Study In Meaning Criteria And The Logic Of Fuzzy Concepts , 1973 .

[18]  Clement T. Yu,et al.  The effect of negation on sentiment analysis and retrieval effectiveness , 2009, CIKM.

[19]  Georg H. Van Wright An essay in modal logic / Georg H. Van Wright , 1951 .

[20]  M. Israel The Pragmatics of Polarity , 2004 .

[21]  Dragomir R. Radev,et al.  Detecting Speculations and their Scopes in Scientific Text , 2009, EMNLP.

[22]  Roser Morante,et al.  Learning the Scope of Hedge Cues in Biomedical Texts , 2009, BioNLP@HLT-NAACL.

[23]  Yuji Matsumoto,et al.  Annotating Event Mentions in Text with Modality, Focus, and Source Information , 2010, LREC.

[24]  Goran Nenadic,et al.  Identification of negated regulation events in the literature: exploring the feature space , 2010, Semantic Mining in Biomedicine.

[25]  Andrew Hickl,et al.  A Discourse Commitment-Based Framework for Recognizing Textual Entailment , 2007, ACL-PASCAL@ACL.

[26]  Dan I. Moldovan,et al.  Semantic Representation of Negation Using Focus Detection , 2011, ACL.

[27]  Raphael Salkie,et al.  Modality in English : theory and description , 2009 .

[28]  G. P. Henderson,et al.  An Essay in Modal Logic. , 1953 .

[29]  Yang Huang,et al.  A novel hybrid approach to automated negation detection in clinical radiology reports. , 2007, Journal of the American Medical Informatics Association : JAMIA.

[30]  See-Kiong Ng,et al.  BioContrasts: extracting and exploiting protein-protein contrastive relations from biomedical literature , 2005, Bioinform..

[31]  Sampo Pyysalo,et al.  BioCause: Annotating and analysing causality in the biomedical domain , 2013, BMC Bioinformatics.

[32]  ACE (Automatic Content Extraction) Chinese Annotation Guidelines for Relations , 2005 .

[33]  Sergei Nirenburg,et al.  Book Review: Ontological Semantics, by Sergei Nirenburg and Victor Raskin , 2004, CL.

[34]  F. Palmer,et al.  Mood and modality , 1986 .

[35]  Chungmin Lee Negation and Focus in English. , 2013 .

[36]  Sanda M. Harabagiu,et al.  Negation, Contrast and Contradiction in Text Processing , 2006, AAAI.

[37]  Alistair Kennedy,et al.  SENTIMENT CLASSIFICATION of MOVIE REVIEWS USING CONTEXTUAL VALENCE SHIFTERS , 2006, Comput. Intell..

[38]  Roser Morante,et al.  SemEval-2010 Task 10: Linking Events and Their Participants in Discourse , 2009, SemEval@ACL.

[39]  Saul A. Kripke,et al.  Semantical Considerations on Modal Logic , 2012 .

[40]  János Csirik,et al.  The BioScope corpus: annotation for negation, uncertainty and their scope in biomedical texts , 2008, BioNLP.

[41]  Roser Morante,et al.  Learning the Scope of Negation in Biomedical Texts , 2008, EMNLP.

[42]  Long H. Ngo,et al.  Implementation and Evaluation of Four Different Methods of Negation Detection , 2007 .

[43]  James Pustejovsky,et al.  FactBank: a corpus annotated with event factuality , 2009, Lang. Resour. Evaluation.

[44]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[45]  Weiwei Guo,et al.  Committed Belief Annotation and Tagging , 2009, Linguistic Annotation Workshop.

[46]  Modality and Language , 2022 .

[47]  Janyce Wiebe,et al.  Computing Attitude and Affect in Text: Theory and Applications , 2005, The Information Retrieval Series.

[48]  Janyce Wiebe,et al.  Learning Subjective Language , 2004, CL.

[49]  Jari Björne,et al.  BioInfer: a corpus for information extraction in the biomedical domain , 2007, BMC Bioinformatics.

[50]  James Pustejovsky,et al.  A factuality profiler for eventualities in text , 2008 .

[51]  Ani Nenkova,et al.  Automatic sense prediction for implicit discourse relations in text , 2009, ACL.

[52]  Nigel Collier,et al.  The GENIA project: corpus-based knowledge acquisition and information extraction from genome research papers , 1999, EACL.

[53]  Hedde Zeijlstra Negation and negative polarity , 2013 .

[54]  Sabine Buchholz,et al.  CoNLL-X Shared Task on Multilingual Dependency Parsing , 2006, CoNLL.

[55]  Owen Rambow,et al.  Automatic Committed Belief Tagging , 2010, COLING.

[56]  Carla Umbach,et al.  On the Notion of Contrast in Information Structure and Discourse Structure , 2004, J. Semant..

[57]  Carol Friedman,et al.  Research Paper: A General Natural-language Text Processor for Clinical Radiology , 1994, J. Am. Medical Informatics Assoc..

[58]  Prakash M. Nadkarni,et al.  Research Paper: Use of General-purpose Negation Detection to Augment Concept Indexing of Medical Documents: A Quantitative Study Using the UMLS , 2001, J. Am. Medical Informatics Assoc..

[59]  Goran Nenadic,et al.  Using SVMs with the Command Relation features to identify negated events in biomedical literature , 2010, NeSp-NLP@ACL.

[60]  Ted Briscoe,et al.  Weakly Supervised Learning for Hedge Classification in Scientific Literature , 2007, ACL.

[61]  Sophia Ananiadou,et al.  Categorising Modality in Biomedical Texts , 2008, LREC 2008.

[62]  Sumithra Velupillai,et al.  How Certain are Clinical Assessments? Annotating Swedish Clinical Text for (Un)certainties, Speculations and Negations , 2010, LREC.

[63]  Chu-Ren Huang,et al.  Evidentiality for Text Trustworthiness Detection , 2010 .

[64]  Ido Dagan,et al.  The Third PASCAL Recognizing Textual Entailment Challenge , 2007, ACL-PASCAL@ACL.

[65]  Victoria L. Rubin Stating with Certainty or Stating with Doubt: Intercoder Reliability Results for Manual Annotation of Epistemically Modalized Statements , 2007, NAACL.

[66]  Janyce Wiebe,et al.  Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2005, HLT.

[67]  Xiaolong Wang,et al.  A Cascade Method for Detecting Hedges and their Scope in Natural Language Text , 2010, CoNLL Shared Task.

[68]  Erik Velldal,et al.  Predicting speculation: a simple disambiguation approach to hedge detection in biomedical literature , 2011, J. Biomed. Semant..

[69]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[70]  Claire Cardie,et al.  OpinionFinder: A System for Subjectivity Analysis , 2005, HLT.

[71]  Michael Grüninger,et al.  Introduction , 2002, CACM.

[72]  Victoria L. Rubin Identifying certainty in texts , 2006 .

[73]  M. de Rijke,et al.  Modal Logic , 2001, Cambridge Tracts in Theoretical Computer Science.

[74]  Claire Cardie,et al.  Annotating Expressions of Opinions and Emotions in Language , 2005, Lang. Resour. Evaluation.

[75]  J. van der Auwera,et al.  Modality’s semantic map , 1998 .

[76]  Stephan Oepen,et al.  Syntactic Scope Resolution in Uncertainty Analysis , 2010, COLING.

[77]  Aris Floratos,et al.  Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm [published erratum appears in Bioinformatics 1998;14(2): 229] , 1998, Bioinform..

[78]  Wendy W. Chapman,et al.  A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries , 2001, J. Biomed. Informatics.

[79]  Ilya M. Goldin,et al.  Learning to Detect Negation with ‘Not’ in Medical Texts , 2003 .

[80]  János Csirik,et al.  The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text , 2010, CoNLL Shared Task.

[81]  Hagit Shatkay,et al.  New directions in biomedical text annotation: definitions, guidelines and corpus construction , 2006, BMC Bioinformatics.

[82]  Mitchell P. Marcus,et al.  Text Chunking using Transformation-Based Learning , 1995, VLC@ACL.

[83]  Johanna Nichols,et al.  Evidentiality: The Linguistic Coding of Epistemology , 1986 .

[84]  Peter L. Elkin,et al.  A controlled trial of automated classification of negation from clinical notes , 2005, BMC Medical Informatics Decis. Mak..

[85]  Oren Etzioni,et al.  Open Information Extraction from the Web , 2007, CACM.

[86]  Natalia Grabar,et al.  Exploitation of speculation markers to identify the structure of biomedical scientific writing , 2009, AMIA.

[87]  Richard Spencer-Smith,et al.  Modal Logic , 2007 .

[88]  Mirella Lapata,et al.  Proceedings of the Fourteenth Conference on Computational Natural Language Learning , 2010, CoNLL 2010.

[89]  E. Herburger Negative contexts'. Collocation, polarity and multiple negation , 2000 .

[90]  Halil Kilicoglu,et al.  Syntactic Dependency Based Heuristics for Biological Event Extraction , 2009, BioNLP@HLT-NAACL.

[91]  Lior Rokach,et al.  Negation recognition in medical narrative reports , 2008, Information Retrieval.

[92]  Annie Zaenen,et al.  Contextual Valence Shifters , 2006, Computing Attitude and Affect in Text.

[93]  Jun'ichi Tsujii,et al.  Corpus annotation for mining biomedical events from literature , 2008, BMC Bioinformatics.

[94]  Doug Downey,et al.  It’s a Contradiction – no, it’s not: A Case Study using Functional Relations , 2008, EMNLP.

[95]  János Csirik,et al.  The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes , 2008, BMC Bioinformatics.

[96]  James Pustejovsky,et al.  Temporal and Event Information in Natural Language Text , 2005, Lang. Resour. Evaluation.

[97]  Wendy W. Chapman,et al.  Evaluation of negation phrases in narrative clinical reports , 2001, AMIA.

[98]  K. Hyland,et al.  Hedging in scientific research articles , 1998 .

[99]  Janyce Wiebe,et al.  Articles: Recognizing Contextual Polarity: An Exploration of Features for Phrase-Level Sentiment Analysis , 2009, CL.

[100]  Padmini Srinivasan,et al.  The Language of Bioscience: Facts, Speculations, and Statements In Between , 2004, HLT-NAACL 2004.

[101]  Dietrich Klakow,et al.  A survey on the role of negation in sentiment analysis , 2010, NeSp-NLP@ACL.

[102]  G. Tottie Negation in English speech and writing : a study in variation , 1993 .

[103]  Guodong Zhou,et al.  A Unified Framework for Scope Learning via Simplified Shallow Semantic Parsing , 2010, EMNLP.

[104]  Robert E. Mercer,et al.  Using Hedges to Classify Citations in Scientific Articles , 2006, Computing Attitude and Affect in Text.

[105]  Christopher D. Manning,et al.  Finding Contradictions in Text , 2008, ACL.

[106]  W. Bruce Croft,et al.  Research Paper: Ad Hoc Classification of Radiology Reports , 1999, J. Am. Medical Informatics Assoc..

[107]  Livio Robaldo,et al.  The Penn Discourse TreeBank 2.0. , 2008, LREC.

[108]  Roser Morante,et al.  Descriptive Analysis of Negation Cues in Biomedical Texts , 2010, LREC.

[109]  Janyce Wiebe,et al.  RECOGNIZING STRONG AND WEAK OPINION CLAUSES , 2006, Comput. Intell..

[110]  Christine D. Piatko,et al.  A Modality Lexicon and its use in Automatic Tagging , 2010, LREC.

[111]  Learning to distinguish valid textual entailments , 2006 .

[112]  Maria Skeppstedt Negation Detection in Swedish Clinical Text , 2010, Louhi@NAACL-HLT.

[113]  Özlem Uzuner,et al.  Machine learning and rule-based approaches to assertion classification. , 2009, Journal of the American Medical Informatics Association : JAMIA.

[114]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[115]  Alan Lee,et al.  Annotating Attribution in the Penn Discourse TreeBank , 2006 .

[116]  Elly Ifantidou,et al.  Evidentials and relevance , 2001 .

[117]  Wendy W. Chapman,et al.  ConText: An algorithm for determining negation, experiencer, and temporal status from clinical reports , 2009, J. Biomed. Informatics.

[118]  Stephan Seifert,et al.  A basic bibliography on negation in natural language , 1987 .

[119]  B. Cornillie Modality , 2019, The SAGE Encyclopedia of Human Communication Sciences and Disorders.

[120]  Otto Jespersen,et al.  The Philosophy of Grammar , 1924 .

[121]  Laurence R. Horn A Natural History of Negation , 1989 .

[122]  György Szarvas,et al.  Hedge Classification in Biomedical Texts with a Weakly Supervised Selection of Keywords , 2008, ACL.

[123]  Veronika Vincze,et al.  Linguistic scope-based and biological event-based speculation and negation annotations in the Genia Event and BioScope corpora , 2010, Semantic Mining in Biomedicine.

[124]  Arnim von Stechow,et al.  Semantik : ein internationales Handbuch der zeitgenössischen Forschung = Semantics : an international handbook of contemporary research , 1991 .

[125]  Arul Menezes,et al.  Effectively Using Syntax for Recognizing False Entailment , 2006, NAACL.

[126]  Ben Medlock,et al.  Exploring hedge identification in biomedical literature , 2008, J. Biomed. Informatics.

[127]  Sampo Pyysalo,et al.  Overview of BioNLP’09 Shared Task on Event Extraction , 2009, BioNLP@HLT-NAACL.

[128]  James Pustejovsky,et al.  SlinkET: A Partial Modal Parser for Events , 2006, LREC.

[129]  Michael Strube,et al.  Finding Hedges by Chasing Weasels: Hedge Detection Using Wikipedia Tags and Shallow Linguistic Features , 2009, ACL.

[130]  Maria Georgescul,et al.  A Hedgehop over a Max-Margin Framework Using Hedge Cues , 2010, CoNLL Shared Task.

[131]  A. Kratzer The Notional Category of Modality , 2008 .

[132]  Massimo Poesio,et al.  Negation of protein-protein interactions: analysis and extraction , 2007, ISMB/ECCB.

[133]  Sophia Ananiadou,et al.  Evaluating a meta-knowledge annotation scheme for bio-events , 2010, NeSp-NLP@ACL.

[134]  Theresa Wilson Fine-grained subjectivity and sentiment analysis: recognizing the intensity, polarity, and attitudes of private states , 2008 .