1,888 research outputs found
GATE -- an Environment to Support Research and Development in Natural Language Engineering
We describe a software environment to support research and development in natural language (NL) engineering. This environment -- GATE (General Architecture for Text Engineering) -- aims to advance research in the area of machine processing of natural languages by providing a software infrastructure on top of which heterogeneous NL component modules may be evaluated and refined individually or may be combined into larger application systems. Thus, GATE aims to support both researchers and developers working on component technologies (e.g. parsing, tagging, morphological analysis) and those working on developing end-user applications (e.g. information extraction, text summarisation, document generation, machine translation, and second language learning). GATE will promote reuse of component technology, permit specialisation and collaboration in large-scale projects, and allow for the comparison and evaluation of alternative technologies. The first release of GATE is now available
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Learning from AI : new trends in database technology
Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database
Efficient Normal-Form Parsing for Combinatory Categorial Grammar
Under categorial grammars that have powerful rules like composition, a simple
n-word sentence can have exponentially many parses. Generating all parses is
inefficient and obscures whatever true semantic ambiguities are in the input.
This paper addresses the problem for a fairly general form of Combinatory
Categorial Grammar, by means of an efficient, correct, and easy to implement
normal-form parsing technique. The parser is proved to find exactly one parse
in each semantic equivalence class of allowable parses; that is, spurious
ambiguity (as carefully defined) is shown to be both safely and completely
eliminated.Comment: 8 pages, LaTeX packaged with three .sty files, also uses cgloss4e.st
CHR Grammars
A grammar formalism based upon CHR is proposed analogously to the way
Definite Clause Grammars are defined and implemented on top of Prolog. These
grammars execute as robust bottom-up parsers with an inherent treatment of
ambiguity and a high flexibility to model various linguistic phenomena. The
formalism extends previous logic programming based grammars with a form of
context-sensitive rules and the possibility to include extra-grammatical
hypotheses in both head and body of grammar rules. Among the applications are
straightforward implementations of Assumption Grammars and abduction under
integrity constraints for language analysis. CHR grammars appear as a powerful
tool for specification and implementation of language processors and may be
proposed as a new standard for bottom-up grammars in logic programming.
To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200
Incremental syntax generation with tree adjoining grammars
With the increasing capacity of AI systems the design of human--computer interfaces has become a favorite research topic in AI. In this paper we focus on aspects of the output of a computer. The architecture of a sentence generation component -- embedded in the WIP system -- is described. The main emphasis is laid on the motivation for the incremental style of processing and the encoding of adequate linguistic units as rules of a Lexicalized Tree Adjoining Grammar with Unification
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