Titlebook: Computing Meaning; Volume 4 Harry Bunt,Johan Bos,Stephen Pulman Book 2014 Springer Science+Business Media Dordrecht 2014 Computational sema

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Abductive Reasoning with a Large Knowledge Base for Discourse Processingthe abductive inference procedure in a system called .. Particular attention is paid to constructing a large and reliable knowledge base for supporting inferences. For this purpose we exploit such lexical-semantic resources as WordNet and FrameNet. English Slot Grammar is used to parse text and prod

北京人起源

Natural Logic and Natural Language Inferencerpretation. We extend past work in ., which has focused on semantic containment and monotonicity, by incorporating both semantic exclusion and implicativity. Our model decomposes an inference problem into a sequence of atomic edits linking premise to hypothesis; predicts a lexical entailment relatio

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Designing Efficient Controlled Languages for Ontologiesh are suitable to be used in natural language front-ends to ontology-based systems. Efficiency in this setting is defined as the tractability (in the sense of computational complexity theory) of logical reasoning in such fragments, measured in the size of the data they aim to manage. In particular,

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A Context-Change Semantics for Dialogue Actsne-grained distinctions to be made between related types of dialogue acts, and relations like entailment and exclusion between dialogue acts to be established. The approach is applied to the inventory of dialogue act types in the DIT. taxonomy, using dialogue act representations as defined in the Di

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VerbNet Class Assignment as a WSD Taskbly, semantic role labeling. Since, in addition to thematic roles, it also provides semantic predicates, it can serve as a foundation for further inferencing. Many verbs belong to multiple VerbNet classes, with each class membership corresponding roughly to a different sense of the verb. A VerbNet t

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Annotation of Compositional Operations with GLML Language (GLML), a mark-up language inspired by the Generative Lexicon model, for identifying such relations. While most annotation systems capture surface relationships, GLML captures the “compositional history” of the argument selection relative to the predicate. We provide a brief overview of GL

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Incremental Recognition and Prediction of Dialogue Actscommunicative functions can be recognized in a data-oriented way on the basis of observable features of communicative behaviour. An incremental, token-based approach is described which combines the use of local classifiers, that exploit local utterance features, and global classifiers that use the o

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Book 2014esearch in computational semantics, including descriptions of new methods for constructing and improving resources for semantic computation, such as WordNet, VerbNet, and semantically annotated corpora. It also presents new statistical methods in semantic computation, such as the application of dist

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Computing Meaning: Annotation, Representation, and Inference, that play an important part in later chapters: (1) the nature of meaning representations; (2) the integration of inferencing with compositional interpretation; and (3) the construction of semantically annotated corpora and their use in machine learning of meaning computation.