"Abstract" Understanding: The Relation between Language and Memory

Natural language is primarily a tool of communication. This implies that whatever roles syntax, semantics, pragmatics, and world knowledge play in language understanding, the comprehension process must be driven by the need to understand the text or conversation, where understand means sufficiently relating the new information being conveyed to existing memories in order to remember the information and/or respond. The need for memory-driven text processing becomes especially clear during designed to read large the construction of a computer system numbers of texts and add them to a coherent memory. However, the recognition that information such as syntax and semantics play only a subsidiary role in text processing does not make understanding more difficult; rather, it makes it possible. A current natural language processing project underway at Columbia involves the creation of a computer program, known as RESEARCHER, that will read large numbers of technical abstracts, such as patent abstracts, and builds up a coherent memory based on the information obtained. This memory is then used in turn to help in the understanding process. RESEARCHER will use some of the same understanding principles as did IPP, a program that reads and remembers news stories [Lebowitz 80, Lebowitz 81]. One of the goals of RESEARCHER is to show that memory-based understanding techniques are as applicable to physical descriptions as to descriptions of events. In fact, due to the knowledge-intensive nature of technical descriptions, it is expected that the application of memory will be even more important in driving processing

What is behind a summary-evaluation decision?

Research in psychology has reported that, among the variety of possibilities for assessment methodologies, summary evaluation offers a particularly adequate context for inferring text comprehension and topic understanding. However, grades obtained in this methodology are hard to quantify objectively. Therefore, we carried out an empirical study to analyze the decisions underlying human summary-grading behavior. The task consisted of expert evaluation of summaries produced in critically relevant contexts of summarization development, and the resulting data were modeled by means of Bayesian networks using an application called Elvira, which allows for graphically observing the predictive power (if any) of the resultant variables. Thus, in this article, we analyzed summary-evaluation decision making in a computational framewor

The Use of Memory in Text Processing

The performance of a natural language processing system should improve as it reads more and more texts. This is true both for systems intended as cognitive models and for practical text processing systems. Permanent long-term memory should be useful during all stages of text understanding. For example, if, while reading a patent abstract about a new disk drive, a system can retrieve information about similar objects from memory, processing should be simplified. However, most natural language programs do not exhibit such learning behavior. We describe in this article how RESEARCHER, a program that reads, remembers and generalizes from patent abstracts, makes use of its automatically generated memory to assist in low-level text processing, primarily involving disambiguation that could be accomplished no other way. We describe both RESEARCHER's basic understanding methods and the integration of memory access. Included is an extended example of RESEARCHER processing a patent abstract by using information about several other abstracts already in memory

Lexicon Design in a German Natural Language. System

The design of a German natural language system for computer-assisted instruction Specifically, the beginnings considered as well as the is of examined in this thesis. such a project are component correctness of a German sentence. A for analyzing the prototype that represents this component is implemented to demonstrate the usefulness of such a system in helping a student to learn the German language. The component consists of a German parser and a German lexicon which forms the basis of the system. T�he German lexicon contains the information about word meanings which enables the parser to recognize a correctly formed sentence and to extract the subject, verb, and object from the sentence.Computing and Information Scienc

Analisador por grafo: superação de incorrecções na escrita do português

Dissertação de Mestrado em Engenharia InformáticaNesta tese é apresentado um sistema constituído por três módulos (um analisador, um formulador de hipóteses e um corrector) que detecta e corrige vários tipos de erros morfosintácticos e que, de algum modo, supera o seu próprio desconhecimento. Assim, dada uma cadeia de caracteres, o sistema tenta classificá-la como uma frase portuguesa gramaticalmente correcta ou sugere correcções baseadas na análise sintáctica que realizou. Este sistema, construído em Prolog, utiliza um analisador por grafo (chart-parser) para pesquisa de constituintes da frase que, em caso de falha, interage com um formulador de hipóteses permitindo assim a superação da mesma. A gramática utilizada, de movimentação e ancoragem, permite a identificação de constituintes fora da ordem canónica e possibilita a sua recolocação na estrutura sintáctica canónica de uma frase tendo em conta alguns tipos de barreiras. O módulo corrector, face ao grafo obtido, considera como mais plausíveis as soluções com menor número de erros. Se existir uma palavra desconhecida com categoria sintáctica atribuída, o módulo corrector invocará um corrector ortográfico muito simplificado (tratando apenas os erros tipificados por Damerau [Dam 64] e utilizando um conjunto de regras que permitem o estabelecimento de preferências relacionadas com confusões fonéticas) que tentará propôr correcções à palavra ou a sua admissão como neologismo