Text, Speech and Language Technology

Computing Meaning: Annotation, Representation, and Inference by Harry Bunt, Johan Bos, and Stephen Pulman . 1 Introduction . 2 About this book . 2.1 Semantic Representation and Compositionality . 2.2 Inference and Understanding . 2.3 Semantic Resources and Annotation . References .- Part I Semantic Representation and Compositionality . Deterministic Statistical Mapping of Sentences to Underspecified Semantics by Hiyan Alshawi, Pi-Chuan Chang, and Michael Ringgaard . 1 Introduction . 2 Direct Semantic Mapping . 3 Semantic Expressions . 3.1 Connectives and Examples . 4 Encoding Semantics as Dependencies . 4.1 Alignment . 4.2 Headedness . 4.3 Label Construction . 5 Experiments . 5.1 Data Preparation . 5.2 Parser . 5.3 Results . 6 Conclusion and Further Work . References .- A formal approach to linking logical form and vector-space lexical semantics by Dan Garrette, Katrin Erk, and Raymond Mooney . 1 Introduction . 2 Background . 3 Linking logical form and vector spaces . 4 Transforming natural language text to logical form . 5 Ambiguity in word meaning . 6 Implicativity . 7 Preliminary Evaluation . 8 Future work . 9 Conclusion . References .- Annotations that effectively contribute to semantic interpretation by Harry Bunt . 1 Introduction: functions of semantic annotations . 2 The semantics of semantic annotations . 2.1 Interpreting annotations expressed in XML . 2.2 The design of semantic annotation languages . 3 Combining semantic annotations and semantic representations . 3.1 Contextualization . 3.2 Semantic alignment . 3.3 Explicitation . 4 Conclusions and perspectives . References .- Concrete Sentence Spaces for Compositional Distributional Models of Meaning by Edward Grefenstette, Mehmoosh Sadrzadeh, Stephen Clark, Bob Coecke, and Stephen Pulman . 1 Introduction . 2 Background . 3 From Truth-Theoretic to Corpus-based Meaning . 4 Concrete Computations . 5 Different Grammatical Structures . 6 Ambiguous Words . 7 Related Work . References .- Part II Inference and Understanding Recognizing Textual Entailment and Computational Semantics by Johan Bos . 1 Introduction . 2 The Logical Method . 2.1 Robust semantic analysis . 2.2 Applying theorem proving . 2.3 Implementation and results . A Critical Evaluation of Performance . 3.1 Proofs found for entailment pairs (true positives) . 3.2 Incorrect proofs found (false positives) . 3.3 Missing proofs (false negatives) . 4 Discussion and Conclusion . References . Abductive Reasoning with a Large Knowledge Base for Discourse Processing by Ekaterina Ovchinnikova, Niloofar Montazeri, Theodore Alexandrov, Jerry R. Hobbs, Michael C. McCord, and Rutu Mulkar-Mehta . 1 Introduction . 2 Weighted Abduction . 3 Discourse Processing Pipeline and Abductive Reasoning . 4 Unification in Weighted Abduction . 5 Knowledge Base . 6 Adapting Mini-TACITUS to a Large Knowledge Base . 6.1 Time and Depth Parameters . 6.2 Filtering out Axioms and Input Propositions . 7 Recognizing Textual Entailment . 8 Experimental Evaluation . 8.1 Weighted Abduction for Recognizing Textual Entailment . 8.2 Semantic Role Labeling . 9 Conclusion and Future Work . References .- Natural logic and natural language inference by Bill MacCartney and Christopher D. Manning . 1 Introduction . 2 An inventory of entailment relations . 3 Joining entailment relations . 4 Lexical entailment relations . 5 Entailment relations and semantic composition . 6 Implicatives and factives . 7 Putting it all together . 8 Implementation and evaluation . 9 Conclusion . References .- Designing Efficient Controlled Languages for Ontologies by Camilo Thorne, Raffaella Bernardi, and Diego Calvanese . 1 Introduction . 2 Controlled Languages and Semantic Complexity . 3 DL-Lite and its Computational Properties . 4 Categorial Grammars . 5 Lite English and its Grammar CG-lite . 5.1 Fragment of Natural Language for DL-Lite . 5.2 Expressing DL-Litecore . 5.3 Expressing DL-LiteR;u . 6 Distribution of Boolean- and non-Boolean-closed Fragments . 7 Related Work . 8 Conclusions . References .- Part III Semantic Resources and Annotation . A Context-Change Semantics for Dialogue Acts by Harry Bunt . 1 Introduction . 2 DiAML: Dialogue Act Markup Language . 2.1 Abstract syntax . 2.2 Concrete Syntax . 2.3 DiAML Semantics . 3 Context Model Structure and Content . 3.1 Types of Context Information . 3.2 Semantic Primitives . 4 Dialogue Act Interpretation . 4.1 The Semantics of Communicative Functions . 4.2 Communicative Function Qualifiers . 5 Conclusion . References .- VerbNet Class Assignment as a WSD Task by Susan Windisch Brown, Dmitriy Dligach and Martha Palmer . 1 Introduction . 2 Related Work . 3 Method . 3.1 The Data . 3.2 Features . 3.3 Experimental Setup . 4 Results . 5 Discussion . 5.1 Contributions of the Features . 5.2 Semlink Annotation . 5.3 Metaphorical Interpetations . 6 Conclusion . 7 Future Work . References .- Annotation of Compositional Operations with GLML by Pustejovsky, Rumshisky, Batiukova, and Moszkowicz . 1 Introduction: Motivation and Previous Work on Semantic . Annotation . 2 Theoretical Preliminaries: Modes of Composition in the Generative Lexicon Theory . 3 Verb-based Annotation. Methodology of Annotation in the Argument Selection and Coercion Task . 3.1 MATTER. 3.2 Task description . 3.3 The Type System for Annotation . 3.4 Corpus Development . 3.5 The Data Format . 4 Noun-based Annotation; Exploiting the Qualia . 4.1 Qualia Selection in Modification Constructions . 4.2 Type Selection Involving Dot Objects . 5 Conclusion . References .- Incremental Recognition and Prediction of Dialogue Acts by Volha Petukhova and Harry Bunt . 1 Introduction . 2 Related work . 3 Set-up of classification experiments . 3.1 Tag set . 3.2 Features and data encoding . 3.3 Classifiers and evaluation metrics . 4 Classification results . 4.1 Joint segmentation and classification . 4.2 Fine-grained incremental interpretation: local classification . 4.3 Managing local classifiers: global classification and global search . 5 Conclusions and future research . References . Index