Robust natural language interpretation requires strong semantic domain models, "fall-soft" recovery heuristics, and very flexible control structures. Although single-strategy parsers have met with a measure of success, a multi.strategy approach is shown to provide a much higher degree of flexibility, redundancy, and ability to bring task-specific domain knowledge (in addition to general linguistic knowledge) to bear on both grammatical and ungrammatical input. A parsing algorithm is presented that integrates several different parsing strategies, with case-frame instantiation dominating. Each of these parsing strategies exploits different types of knowledge; and their combination provides a strong framework in which to process conjunctions, ...
This paper compares two techniques for robust parsing of extragrammatical natural language. Both ...
Most natural language parsers require their input to be grammatical. This significantly constrains t...
In this paper we will present an approach to natural language processing which we define as "hybrid"...
Robust natural language interpretation requires strong semantic domain models, "fail-soft" recovery ...
We describe a new algorithm for table-driven parsing with context-free grammars designed to support ...
Robustness is a key issue for natural language processing in general and parsing in partic-ular, and...
We describe a new algorithm for table-driven parsing with context-free grammars designed to support ...
Practical natural language interfaces must exhibit robust behaviour in the presence of extragrammati...
Practical natural language interfaces must exhibit robust behaviour in the presence of extragrammati...
Practical natural language interfaces must exhibit robust behaviour in the presence of extragrammat...
AbstractWe present a new model of natural language processing in which natural language parsing and ...
Most artificial natural language processing (NLP) systems make use of some simple algorithm for pars...
This dissertation defends in some small measure the thesis that there is a universal parsing model f...
We propose a novel model for parsing natural language sentences into their for-mal semantic represen...
Parsing natural language is an attempt to discover some structure in a text (or textual representati...
This paper compares two techniques for robust parsing of extragrammatical natural language. Both ...
Most natural language parsers require their input to be grammatical. This significantly constrains t...
In this paper we will present an approach to natural language processing which we define as "hybrid"...
Robust natural language interpretation requires strong semantic domain models, "fail-soft" recovery ...
We describe a new algorithm for table-driven parsing with context-free grammars designed to support ...
Robustness is a key issue for natural language processing in general and parsing in partic-ular, and...
We describe a new algorithm for table-driven parsing with context-free grammars designed to support ...
Practical natural language interfaces must exhibit robust behaviour in the presence of extragrammati...
Practical natural language interfaces must exhibit robust behaviour in the presence of extragrammati...
Practical natural language interfaces must exhibit robust behaviour in the presence of extragrammat...
AbstractWe present a new model of natural language processing in which natural language parsing and ...
Most artificial natural language processing (NLP) systems make use of some simple algorithm for pars...
This dissertation defends in some small measure the thesis that there is a universal parsing model f...
We propose a novel model for parsing natural language sentences into their for-mal semantic represen...
Parsing natural language is an attempt to discover some structure in a text (or textual representati...
This paper compares two techniques for robust parsing of extragrammatical natural language. Both ...
Most natural language parsers require their input to be grammatical. This significantly constrains t...
In this paper we will present an approach to natural language processing which we define as "hybrid"...