��We describe a comprehensive framework for text un- derstanding, based on the representation of context. It is designed to serve as a representation of semantics for the full range of in- terpretive and inferential needs of general natural language pro- cessing. Its most distinctive feature is its uniform representation of the various simple and independent linguistic sources that play a role in determining meaning: lexical associations, syntactic re- strictions, case-role expectations, and most importantly, contextual effects. Compositional syntactic structure from a shallow parsing is represented in a neural net-based associative memory, where it then interacts through a Bayesian network with semantic associa- tions and the context or “gist” of the passage carried forward from preceding sentences. Experiments with more than 2000 sentences in different languages are included.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Dynamic Context Generation for Natural Language Understanding: A Multifaceted Knowledge Approach.James Franklin & S. W. K. Chan - 2003 - IEEE Transactions on Systems, Man and Cybernetics Part A 33:23-41.
Logical Reasoning in Natural Language: It is All About Knowledge. [REVIEW]Lucja Iwańska - 1993 - Minds and Machines 3 (4):475-510.
Coordinating Understanding and Generation in an Abductive Approach.Matthew Stone & Richmond H. Thomason - unknown
Natural Language Processing Using a Propositional Semantic Network with Structured Variables.Syed S. Ali & Stuart C. Shapiro - 1993 - Minds and Machines 3 (4):421-451.
An Ontology-Based Approach to Metaphor Cognitive Computation.Xiaoxi Huang, Huaxin Huang, Beishui Liao & Cihua Xu - 2013 - Minds and Machines 23 (1):105-121.
The Representation of Context: Ideas From Artiﬁcial Intelligence.James Franklin - 2003 - Law, Probability and Risk 2:191-199.
Dynamic Interpretation and HOARE Deduction.Jan Eijck & Fer-Jan Vries - 1992 - Journal of Logic, Language and Information 1 (1):1-44.
Syntactic Semantics: Foundations of Computational Natural Language Understanding.William J. Rapaport - 1988 - In James H. Fetzer (ed.), Aspects of AI. Kluwer Academic Publishers.
Natural Language Grammar Induction Using a Constituent-Context Model.Christopher Manning - manuscript
Context in Language Learning and Language Understanding.Kirsten Malmkjær & John Williams (eds.) - 1998 - Cambridge University Press.
Natural Language Grammar Induction Using a Constituent-Context Model.Dan Klein & Christopher D. Manning - unknown
Added to index2010-12-22
Total downloads23 ( #218,570 of 2,168,639 )
Recent downloads (6 months)1 ( #346,816 of 2,168,639 )
How can I increase my downloads?