Natural Language Processing: The PLNLP Approach [electronic resource] /

Natural language is easy for people and hard for machines. For two generations, the tantalizing goal has been to get computers to handle human languages in ways that will be compelling and useful to people. Obstacles are many and legendary. Natural Language Processing: The PLNLP Approach describes one group's decade of research in pursuit of that goal. A very broad coverage NLP system, including a programming language (PLNLP) development tools, and analysis and synthesis components, was developed and incorporated into a variety of well-known practical applications, ranging from text critiquing (CRITIQUE) to machine translation (e.g. SHALT). This books represents the first published collection of papers describing the system and how it has been used. Twenty-six authors from nine countries contributed to this volume. Natural language analysis, in the PLNLP approach, is done is six stages that move smoothly from syntax through semantics into discourse. The initial syntactic sketch is provided by an Augmented Phrase Structure Grammar (APSG) that uses exclusively binary rules and aims to produce some reasonable analysis for any input string. Its `approximate' analysis passes to the reassignment component, which takes the default syntactic attachments and adjusts them, using semantic information obtained by parsing definitions and example sentences from machine-readable dictionaries. This technique is an example of one facet of the PLNLP approach: the use of natural language itself as a knowledge representation language -- an innovation that permits a wide variety of online text materials to be exploited as sources of semantic information. The next stage computes the intrasential argument structure and resolves all references, both NP- and VP-anaphora, that can be treated at this point in the processing. Subsequently, additional components, currently not so well developed as the earlier ones, handle the further disambiguation of word senses, the normalization of paraphrases, and the construction of a paragraph (discourse) model by joining sentential semantic graphs. Natural Language Processing: The PLNLP Approach acquaints the reader with the theory and application of a working, real-world, domain-free NLP system, and attempts to bridge the gap between computational and theoretical models of linguistic structure. It provides a valuable resource for students, teachers, and researchers in the areas of computational linguistics, natural processing, artificial intelligence, and information science.

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Main Authors: Jensen, Karen. editor., Heidorn, George E. editor., Richardson, Stephen D. editor., SpringerLink (Online service)
Format: Texto biblioteca
Language:eng
Published: Boston, MA : Springer US, 1993
Subjects:Computer science., Artificial intelligence., Computational linguistics., Computer Science., Language Translation and Linguistics., Artificial Intelligence (incl. Robotics)., Computational Linguistics.,
Online Access:http://dx.doi.org/10.1007/978-1-4615-3170-8
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id KOHA-OAI-TEST:218800
record_format koha
institution COLPOS
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
En linea
databasecode cat-colpos
tag biblioteca
region America del Norte
libraryname Departamento de documentación y biblioteca de COLPOS
language eng
topic Computer science.
Artificial intelligence.
Computational linguistics.
Computer Science.
Language Translation and Linguistics.
Artificial Intelligence (incl. Robotics).
Computational Linguistics.
Computer science.
Artificial intelligence.
Computational linguistics.
Computer Science.
Language Translation and Linguistics.
Artificial Intelligence (incl. Robotics).
Computational Linguistics.
spellingShingle Computer science.
Artificial intelligence.
Computational linguistics.
Computer Science.
Language Translation and Linguistics.
Artificial Intelligence (incl. Robotics).
Computational Linguistics.
Computer science.
Artificial intelligence.
Computational linguistics.
Computer Science.
Language Translation and Linguistics.
Artificial Intelligence (incl. Robotics).
Computational Linguistics.
Jensen, Karen. editor.
Heidorn, George E. editor.
Richardson, Stephen D. editor.
SpringerLink (Online service)
Natural Language Processing: The PLNLP Approach [electronic resource] /
description Natural language is easy for people and hard for machines. For two generations, the tantalizing goal has been to get computers to handle human languages in ways that will be compelling and useful to people. Obstacles are many and legendary. Natural Language Processing: The PLNLP Approach describes one group's decade of research in pursuit of that goal. A very broad coverage NLP system, including a programming language (PLNLP) development tools, and analysis and synthesis components, was developed and incorporated into a variety of well-known practical applications, ranging from text critiquing (CRITIQUE) to machine translation (e.g. SHALT). This books represents the first published collection of papers describing the system and how it has been used. Twenty-six authors from nine countries contributed to this volume. Natural language analysis, in the PLNLP approach, is done is six stages that move smoothly from syntax through semantics into discourse. The initial syntactic sketch is provided by an Augmented Phrase Structure Grammar (APSG) that uses exclusively binary rules and aims to produce some reasonable analysis for any input string. Its `approximate' analysis passes to the reassignment component, which takes the default syntactic attachments and adjusts them, using semantic information obtained by parsing definitions and example sentences from machine-readable dictionaries. This technique is an example of one facet of the PLNLP approach: the use of natural language itself as a knowledge representation language -- an innovation that permits a wide variety of online text materials to be exploited as sources of semantic information. The next stage computes the intrasential argument structure and resolves all references, both NP- and VP-anaphora, that can be treated at this point in the processing. Subsequently, additional components, currently not so well developed as the earlier ones, handle the further disambiguation of word senses, the normalization of paraphrases, and the construction of a paragraph (discourse) model by joining sentential semantic graphs. Natural Language Processing: The PLNLP Approach acquaints the reader with the theory and application of a working, real-world, domain-free NLP system, and attempts to bridge the gap between computational and theoretical models of linguistic structure. It provides a valuable resource for students, teachers, and researchers in the areas of computational linguistics, natural processing, artificial intelligence, and information science.
format Texto
topic_facet Computer science.
Artificial intelligence.
Computational linguistics.
Computer Science.
Language Translation and Linguistics.
Artificial Intelligence (incl. Robotics).
Computational Linguistics.
author Jensen, Karen. editor.
Heidorn, George E. editor.
Richardson, Stephen D. editor.
SpringerLink (Online service)
author_facet Jensen, Karen. editor.
Heidorn, George E. editor.
Richardson, Stephen D. editor.
SpringerLink (Online service)
author_sort Jensen, Karen. editor.
title Natural Language Processing: The PLNLP Approach [electronic resource] /
title_short Natural Language Processing: The PLNLP Approach [electronic resource] /
title_full Natural Language Processing: The PLNLP Approach [electronic resource] /
title_fullStr Natural Language Processing: The PLNLP Approach [electronic resource] /
title_full_unstemmed Natural Language Processing: The PLNLP Approach [electronic resource] /
title_sort natural language processing: the plnlp approach [electronic resource] /
publisher Boston, MA : Springer US,
publishDate 1993
url http://dx.doi.org/10.1007/978-1-4615-3170-8
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spelling KOHA-OAI-TEST:2188002018-07-30T23:55:29ZNatural Language Processing: The PLNLP Approach [electronic resource] / Jensen, Karen. editor. Heidorn, George E. editor. Richardson, Stephen D. editor. SpringerLink (Online service) textBoston, MA : Springer US,1993.engNatural language is easy for people and hard for machines. For two generations, the tantalizing goal has been to get computers to handle human languages in ways that will be compelling and useful to people. Obstacles are many and legendary. Natural Language Processing: The PLNLP Approach describes one group's decade of research in pursuit of that goal. A very broad coverage NLP system, including a programming language (PLNLP) development tools, and analysis and synthesis components, was developed and incorporated into a variety of well-known practical applications, ranging from text critiquing (CRITIQUE) to machine translation (e.g. SHALT). This books represents the first published collection of papers describing the system and how it has been used. Twenty-six authors from nine countries contributed to this volume. Natural language analysis, in the PLNLP approach, is done is six stages that move smoothly from syntax through semantics into discourse. The initial syntactic sketch is provided by an Augmented Phrase Structure Grammar (APSG) that uses exclusively binary rules and aims to produce some reasonable analysis for any input string. Its `approximate' analysis passes to the reassignment component, which takes the default syntactic attachments and adjusts them, using semantic information obtained by parsing definitions and example sentences from machine-readable dictionaries. This technique is an example of one facet of the PLNLP approach: the use of natural language itself as a knowledge representation language -- an innovation that permits a wide variety of online text materials to be exploited as sources of semantic information. The next stage computes the intrasential argument structure and resolves all references, both NP- and VP-anaphora, that can be treated at this point in the processing. Subsequently, additional components, currently not so well developed as the earlier ones, handle the further disambiguation of word senses, the normalization of paraphrases, and the construction of a paragraph (discourse) model by joining sentential semantic graphs. Natural Language Processing: The PLNLP Approach acquaints the reader with the theory and application of a working, real-world, domain-free NLP system, and attempts to bridge the gap between computational and theoretical models of linguistic structure. It provides a valuable resource for students, teachers, and researchers in the areas of computational linguistics, natural processing, artificial intelligence, and information science.Natural language is easy for people and hard for machines. For two generations, the tantalizing goal has been to get computers to handle human languages in ways that will be compelling and useful to people. Obstacles are many and legendary. Natural Language Processing: The PLNLP Approach describes one group's decade of research in pursuit of that goal. A very broad coverage NLP system, including a programming language (PLNLP) development tools, and analysis and synthesis components, was developed and incorporated into a variety of well-known practical applications, ranging from text critiquing (CRITIQUE) to machine translation (e.g. SHALT). This books represents the first published collection of papers describing the system and how it has been used. Twenty-six authors from nine countries contributed to this volume. Natural language analysis, in the PLNLP approach, is done is six stages that move smoothly from syntax through semantics into discourse. The initial syntactic sketch is provided by an Augmented Phrase Structure Grammar (APSG) that uses exclusively binary rules and aims to produce some reasonable analysis for any input string. Its `approximate' analysis passes to the reassignment component, which takes the default syntactic attachments and adjusts them, using semantic information obtained by parsing definitions and example sentences from machine-readable dictionaries. This technique is an example of one facet of the PLNLP approach: the use of natural language itself as a knowledge representation language -- an innovation that permits a wide variety of online text materials to be exploited as sources of semantic information. The next stage computes the intrasential argument structure and resolves all references, both NP- and VP-anaphora, that can be treated at this point in the processing. Subsequently, additional components, currently not so well developed as the earlier ones, handle the further disambiguation of word senses, the normalization of paraphrases, and the construction of a paragraph (discourse) model by joining sentential semantic graphs. Natural Language Processing: The PLNLP Approach acquaints the reader with the theory and application of a working, real-world, domain-free NLP system, and attempts to bridge the gap between computational and theoretical models of linguistic structure. It provides a valuable resource for students, teachers, and researchers in the areas of computational linguistics, natural processing, artificial intelligence, and information science.Computer science.Artificial intelligence.Computational linguistics.Computer Science.Language Translation and Linguistics.Artificial Intelligence (incl. Robotics).Computational Linguistics.Springer eBookshttp://dx.doi.org/10.1007/978-1-4615-3170-8URN:ISBN:9781461531708