A Massively Parallel Architecture for Natural Language Parsing – Some Results

1998 ◽  
pp. 93-100
Author(s):  
Raul Sidnei Wazlawick ◽  
José Gabriel Pereira Lopes
Keyword(s):  
Natural Language ◽  
Parallel Architecture ◽  
Massively Parallel ◽  
Natural Language Parsing

Parsing

2017 ◽  
Author(s):  
John Carroll
Keyword(s):  
Natural Language ◽  
Dependency Parsing ◽  
Grammatical Structure ◽  
Linguistic Information ◽  
Natural Language Parsing ◽  
Feature Structures ◽  
Key Concepts ◽  
Learning From Text ◽  
Dependency Structures ◽  
Context Free

This chapter introduces key concepts and techniques for natural-language parsing: that is, finding the grammatical structure of sentences. The chapter introduces the fundamental algorithms for parsing with context-free (CF) phrase structure grammars, how these deal with ambiguous grammars, and how CF grammars and associated disambiguation models can be derived from syntactically annotated text. It goes on to consider dependency analysis, and outlines the main approaches to dependency parsing based both on manually written grammars and on learning from text annotated with dependency structures. It finishes with an overview of techniques used for parsing with grammars that use feature structures to encode linguistic information.

scholarly journals Connectionist natural language parsing

2002 ◽  
Vol 6 (10) ◽  
pp. 437-442 ◽  
Author(s):  
Dominic Palmer-Brown ◽  
Jonathan A. Tepper ◽  
Heather M. Powell
Keyword(s):  
Natural Language ◽  
Natural Language Parsing

scholarly journals Contralog: a Prolog conform forward-chaining environment and its application for dynamic programming and natural language parsing

2016 ◽  
Vol 8 (1) ◽  
pp. 41-62
Author(s):  
Imre Kilián
Keyword(s):  
Dynamic Programming ◽  
Natural Language ◽  
Inference Engine ◽  
Recursive Definition ◽  
Target Model ◽  
Forward Chaining ◽  
Natural Language Parsing ◽  
Multiplication Problem ◽  
Inference Strategy ◽  
Definition Of

Abstract The backward-chaining inference strategy of Prolog is inefficient for a number of problems. The article proposes Contralog: a Prolog-conform, forward-chaining language and an inference engine that is implemented as a preprocessor-compiler to Prolog. The target model is Prolog, which ensures mutual switching from Contralog to Prolog and back. The Contralog compiler is implemented using Prolog's de facto standardized macro expansion capability. The article goes into details regarding the target model. We introduce first a simple application example for Contralog. Then the next section shows how a recursive definition of some problems is executed by their Contralog definition automatically in a dynamic programming way. Two examples, the well-known matrix chain multiplication problem and the Warshall algorithm are shown here. After this, the inferential target model of Prolog/Contralog programs is introduced, and the possibility for implementing the ReALIS natural language parsing technology is described relying heavily on Contralog's forward chaining inference engine. Finally the article also discusses some practical questions of Contralog program development.

Automatic Extraction of Valency Information

1995 ◽  
Vol 107-108 ◽  
pp. 89-111
Author(s):  
Jan Daugaard ◽  
Sabine Kirchmeier-Andersen ◽  
Lene Schøsler
Keyword(s):  
Natural Language ◽  
Research Team ◽  
Corpus Analysis ◽  
Automatic Extraction ◽  
The Past ◽  
Natural Language Parsing ◽  
Theoretical Assumptions ◽  
The Creation

Abstract The above research team has for the past 4 years been working on a database of valency schemes for 4,000 Danish verbs. First we present the underlying theoretical assumptions for the creation of valency schemes. Then the tools to perform automatic extraction of valency information from corpora are described. Finally, the results are presented. Keywords: natural language parsing, Danish, lexical valency, the Pronominal Approach, corpus analysis.

scholarly journals Deep Learning for Natural Language Parsing

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 131363-131373 ◽  
Author(s):  
Sardar Jaf ◽  
Calum Calder
Keyword(s):  
Deep Learning ◽  
Natural Language ◽  
Natural Language Parsing
Sign in / Sign up

Export Citation Format

Share Document