Natural Language Analysis Research Articles

Dynamic interpretation and hoare deduction

In this paper we present a dynamic assignment language which extends the dynamic predicate logic of Groenendijk and Stokhof [1991: 39–100] with ι assignment and with generalized quantifiers. The use of this dynamic assignment language for natural language analysis, along the lines of o.c. and [Barwise, 1987: 1–29], is demonstrated by examples. We show that our representation language permits us to treat a wide variety of ‘donkey sentences’: conditionals with a donkey pronoun in their consequent and quantified sentences with donkey pronouns anywhere in the scope of the quantifier. It is also demonstrated that our account does not suffer from the so-called proportion problem.

Mind and emotion: Children's understanding of the emotional consequences of beliefs and desires

We investigated preschool children's understanding of mind and emotion by examining their understanding that emotions such as happiness and surprise depend on the actor's desires and beliefs. We report four investigations: a study of 3‐year‐olds' ratings of actors' happiness and surprise, a natural language analysis of adults' use of the word surprise in conversation to a preschool child, and two studies of 3‐and 4‐year‐olds' abilities to explain the causes of desire‐dependent and belief‐dependent emotional reactions, such as happiness and surprise respectively. We demonstrate that children as young as 3 years appropriately understand the relevant mental states underlying happiness, sadness, surprise and curiosity, although they misunderstand the usage of some related lexical terms, especially surprise. The findings are discussed with regard to the early development of children's understanding of emotion and their understanding of mind, including children's early understanding of the notion of belief and their ability to distinguish beliefs from desires.

Recent developments in machine translation

This paper describes developments in the area of machine translation (MT). First, the paper gives an overview of developments in Germany in general; then, special problems are discussed. The system taken as an example is METAL (Machine Translation and Analysis of Natural Language), where recent development work has centered around two main topics. (i) Efforts have been made to make the system really multilingual. The German-to-English prototype had to be expanded, some system components had to be readjusted, and additional problems had to be solved. Currently, analysis and synthesis components for German, English, French, Spanish, and Dutch are under development. All these languages use a common system kernel and a standard interface structure. (ii) The system had to be made user-friendly. This was an even more important task as, up to now, MT systems have not been well accepted by users. METAL tries to be more realistic, and also tries to support the main user interfaces in a much better way than has been done before. This is based on the conviction that there are several parameters which determine the real success of an MT system. It is not just translation quality which is decisive, it is also the integration of an MT system into the whole process of preparing and translating documents.

SCISOR: extracting information from on-line news

The future of natural language text processing is examined in the SCISOR prototype. Drawing on artificial intelligence techniques, and applying them to financial news items, this powerful tool illustrates some of the future benefits of natural language analysis through a combination of bottom-up and top-down processing.

On the parallel complexity of discrete relaxation in constraint satisfaction networks

Constraint satisfaction networks have been shown to be a very useful tool for knowledge representation in Artificial Intelligence applications. These networks often utilize local constraint propagation techniques to achieve local consistency (consistent labeling in vision). Such methods have been used extensively in the context of image understanding and interpretation, as well as planning, natural language analysis and truth maintenance systems. In this paper we study the parallel complexity of discrete relaxation, one of the most commonly used constraint propagation techniques. Since the constraint propagation procedures such as discrete relaxation appear to operate locally, it has been previously believed that the relaxation approach for achieving local consistency has a natural parallel solution. Our analysis suggests that a parallel solution is unlikely to improve the known sequential solutions by much. Specifically, we prove that the problem solved by discrete relaxation (arc consistency) is log-space complete for P (the class of polynomial-time deterministic sequential algorithms). Intuitively, this implies that discrete relaxation is inherently sequential and it is unlikely that we can solve the polynomial-time version of the consistent labeling problem in logarithmic time by using only a polynomial number of processors. Some practical implications of our result are discussed. We also provide a two-way transformation between AND/OR graphs, propositional Horn satisfiability and local consistency in constraint networks that allows us to develop optimal linear-time algorithms for local consistency in constraint networks.

Feature grammars for semantic analysis

In this paper, we present a formalism called feature grammar and its application to several problems of semantic analysis. Our extension concerns the structure of the feature value sets, which can be complex, and the definition of unification, which is dependent on this structure. Moreover, we introduce generation rules for feature symbols in order to determine well‐formed symbols, which form the alphabet of a formal language for natural language analysis.

A Mandarin dictation machine based upon a hierarchical recognition approach and Chinese natural language analysis

An experimental Mandarin dictation machine for inputting Mandarin speech (spoken Chinese language) into computers is described. Because of the special characteristics of the Chinese language, syllables are chosen as the basic units for dictation. The machine is designed based on a hierarchical language recognition approach in which acoustic signals are first recognized as a sequence of syllables, possible word hypotheses are then formed from the syllables, and the complete sentences are finally obtained. This approach is implemented by two subsystems. The first recognizes the syllables using speech signal processing techniques, the second subsystem then identifies the exact characters from the syllable and corrects the errors in syllable recognition. The detailed syllable recognition algorithms, word formation rules, parser, grammar, and the syntactic checking algorithms are described. With newspaper text in the form of isolated syllables as input, the preliminary test results indicate that such a dictation machine is not only practically attractive, but technically feasible.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

DISLOG: programming in logic with discontinuities

In this paper, we present an extension to PROLOG we call DISLOG which is designed to deal with relations between non‐contiguous elements in a structure. This extension turns out to be well suited for syntactic analysis of natural and artificial languages. It is also well adapted to express traversal constraints in applications such as planning and expert systems and deductive systems involving, for example, temporal reasoning, DISLOG belongs to the constrained logic programming paradigm and turns out to be more declarative, transparent, and simple than PROLOG to deal with longdistance relations.

Robert Bull and Krister Segerberg. Basic modal logic. Handbook of philosophical logic, Volume II, Extensions of classical logic, edited by D. Gabbay and F. Guenthner, Synthese library, vol. 165, D. Reidel Publishing Company, Dordrecht, Boston, and Lancaster, 1984, pp. 1–88. - John P. Burgess. Basic tense logic. Handbook of philosophical logic, Volume II, Extensions of classical logic, edited by D.

This handbook provides a systematic survey of the central areas of philosophical logic. It is divided into four volumes, each devoted to a major sub-field within the disciplines. The articles should be of value to general philosophers, linguists, logicians, mathematicians and computer scientists. Volume 1, Elements of Classical Logic, deals with the background to what has come to be considered the standard formulation of predicate logic - both as far as its semantics and proof theory are concerned. The central chapter on predicate logic is followed by chapters outlining various alternative, but essentially equivalent ways of constructing the semantics for first-order logic as well as its proof theory. In addition, this volume contains a discussion of higher-order extensions of first-order logic and a compendium of the algorithmic and decision-theoretic prerequisites in the study of logical systems. Volume 2, Extensions of Classical Logic, surveys the most significant extensions of predicate logic and their applications to various philosophical fields of inquiry. The 12 chapters in this volume together provide a succinct introduction to a variety of intensional frameworks, a discussion of the most well-known logical systems, as well as an overview of major applications and of the open problems in the respective fields. Volume 3, Alternatives to Classical Logic, consists of a series of surveys of some of the alternatives to the basic assumptions of classical logic. These include many-valued logic, partial logic, free logic, relevance and entailment logics, dialogue logic, quantum logic and intuitionism. Volume 4, Topics in the Philosophy of Language, presents a panorama of the applications of logical tools and methods in the formal analysis of natural language. Since a number of developments in philosophical logic were originally stimulated by concern arising in the semantic analysis of natural language discourse, the chapters in this volume provide some criteria of evaluation of the applications of work in philosophical logic. In revealing both the adequacies and inadequacies of logical investigations in the semantic structures of natural discourse, these chapters also point the way to future developments in philosophical logic in general and thus close again the circle of inquiry relating logic and language.

Natural language analysis by stochastic optimization: a progress report on Project APRIL

Abstract Parsing techniques based on rules defining grammaticality are difficult to use with authentic natural-language inputs, which are often grammatically messy. Instead, the APRIL system seeks a labelled tree structure which maximizes a numerical measure of conformity to statistical norms derived from a sample of parsed text. No distinction between legal and illegal trees arises: any labelled tree has a value. Because the search space is large and has an irregular geometry, APRIL seeks the best tree using simulated annealing, a stochastic optimization technique. Beginning with an arbitrary tree, many randomly-generated local modifications are considered and adopted or rejected according to their effect on tree-value: acceptance decisions are made probabilistically, subject to a bias against adverse moves which is very weak at the outset but is made to increase as the random walk through the search space continues. This enables the system to converge on the global optimum without getting trapped in local optima. Performance of an early version of the APRIL system on authentic inputs has been yielding analyses with a mean accuracy upwards of 75%, using a schedule which increases processing linearly with sentence-length; modifications currently being implemented should eliminate many of the remaining errors.

Book review: Partiality, Truth and Persistence by Tore Langholm (Lecture Notes 15 Ctr. for the Study of Lang. and Information. University of Chicago Press)

Partiality, Truth and Persistence is the latest in a recent series of inexpensive, softcover lecture notes which deal with various aspects of logic and language. There are several works on natural language processing in the series, but most are rather theoretical studies of logic, especially computational logic. The remainder in the sixteen-title series deal with both topics, such as Pereira and Shieber's Prolog and Natural Language Analysis (Lecture Notes 10).

Computerized content analysis of natural language

The Gottschalk-Gleser Content Analysis Scales have been found to be a transculturally valid and reliable method of measuring the magnitude of a group of psychological states and traits from the content analysis of natural language, and as such these Scales have been found quite useful in medical and psychiatric research. Their use, however, requires time-consuming training of content analysis technicians to code scorable clauses at a correlation level of at least 0.80 with experts. A review of research aimed at the development of computer software, based on LISP, to score typescripts of speech samples on the Gottschalk-Gleser Scales has shown that such computerization is feasible and efficient for the Anxiety and Hostility Scales. The Cognitive Impairment and Social Alienation - Personal Disorganization Scales, however, require more study and research.

Computers in Intellectual History: Lexical Statistics and the Analysis of Political Discourse

Computers in Intellectual History: Lexical Statistics and the Analysis of Political Discourse In I981, Bouwsma pointed out to readers of this Journal that intellectual was becoming and strange field of historical activity. This new intellectual history, he went on to argue, is based on the history of meanings. Two disciplines, he predicted, would be necessary for the development of intellectual in this direction: cultural anthropology and linguistics. Although the achievements of historians, inspired by the work of cultural anthropologists, including Darnton and Ginzburg, are well known, historical use of linguistics methods is less frequent. Bouwsma nevertheless suggested that the connections between language and meanings were of fundamental importance to historians as well as to social scientists. The study of language, he concluded, is likely to become a major tool of the new intellectual history.' Bouwsma's call for of meanings based in part on the historical analysis of natural language comes at time when linguists and literary scholars are using computer-assisted techniques to explore language. The appearance of increasingly powerful microcomputers, sophisticated software, and string processing languages makes language processing less expensive and more effective. Following brief discussion of the theoretical background of applying linguistic analysis to intellectual history, this research note outlines our use of computers to perform quantitative analysis of political language. Although the limitations of such an approach are evident, in some cases quantitative analysis

電気回路の知的CAIのための自然言語理解による解答診断機能

電気回路の知的CAIのための自然言語理解による解答診断機能

Distinguishing Thinking-Feeling Preferences Through the Content Analysis of Natural Language

This article investigates the relationship between natural language and personality characteristics. In particular, an effort was made to determine whether "thinkers" and "feelers," as defined by Jung's typologies, differ in terms of the language they use to express themselves. First, a linguistic content analysis scale was developed. Next, 5-min verbal samples were obtained from subjects and content analyzed. Content analysis scores were correlated with subjects' self-evaluations and their scores on the Thinking-Feeling scale of the Myers-Briggs Type Indicator (MBTI). Gender differences relating to thinking-feeling preferences were also investigated. Significant correlations between content analysis and MBTI scores were obtained, suggesting that valid information regarding individual preferences for thinking versus feeling may be obtained through the analysis of natural language. Males and females differed significantly in terms of their MBTI scores and self-evaluations, but not in their content analysis scores.

A parallel parsing system for natural language analysis

The paper presents a parallel parsing system for Definite Clause Grammars suitable for committed-choice parallel logic programming languages. Grammatical elements such as words and nonterminal symbols are defined as parallel processes. Parsing is done by the processcommunication. The advantage of the system is that all the grammar rules are compiled into the parallel logic programming language and the program has neither any side-effect nor duplicated computation.

Cooperating rewrite processes for natural-language analysis

General methods for understanding a natural language based on the intensive use of rewrite rules and on the existence of several cooperating processes are put forward. The choice of Horn-clause logic as the underlying formalism for semantic representations, together with the employment of unification as pattern-matching procedure and depth-first search with backtracking were derived from logic-programming ideas, in particular from the use of PROLOG. Several examples are presented to illustrate how these methods work.

An experimental logic based on the fundamental deduction principle

Experimental logic can be viewed as a branch of logic dealing with the actual construction of useful deductive systems and their application to various scientific disciplines. In this paper we describe an experimental deductive system called the SYMbolic EVALuator (i.e. SYMEVAL) which is based on a rather simple, yet startling principle about deduction, namely that deduction is fundamentally a process of replacing expressions by logically equivalent expressions. This principle applies both to logical and domain-dependent axioms and rules. Unlike more well-known logical inference systems which do not satisfy this principle, herein is described a system of logical axioms and rules called the SYMMETRIC LOGIC which is based on this principle. Evidence for this principle is given by proving theorems and performing deduction in the areas of set theory, logic programming, natural language analysis, program verification, automatic complexity analysis, and inductive reasoning.

Imputations and Explications: Representational problems in treatments of prepositional attitudes

The representation of propositional attitudes (beliefs, desires, etc.) and the analysis of natural-language, propositional-attitude reports presents difficult problems for cognitive science and artificial intelligence. In particular, various representational approaches to attitudes involve the incorrect “imputation,” to cognitive agents, of the use of artificial theoryladen notions. Interesting cases of this problem are shown to occur in several approaches to attitudes. The imputation problem is shown to arise from the way that representational approaches explicate properties and relationships, and in particular from the way they explicate propositional attitudes themselves. Another factor contributing to imputation is the compositional nature of typical semantic approaches to propositional-attitude reports. Some strategies for avoiding undesirable imputation are examined. One of the main conclusions is that the importance of imputations that arise in a representation scheme depends strongly on the use to which the scheme is put—on whether, for instance, the scheme is used as part of a formal, objective account of natural language, or is used rather as a representational tool within an agent.

Pattern recognition, image processing and computer vision in fifth generation computer systems

It is well-known that one of the goals of research for the last two decades or so in pattern recognition and its sub-areas, such as processing, analysis and understanding of image, speech and natural language, and computer vision techniques etc., has always been to develop fundamental techniques for flexible interactive intelligent man-machine interfaces for computers. In this paper, the author tries to argue that for the evolution of fifth generation computer systems (FGCS) as defined by Japanese scientists, some of the things required are realisation and implementation of the advances in pattern recognition and its sub-areas, not only to achieve the man-machine interface with a natural mode of communication, but also for the realisation of the basic mechanisms of inference, association and learning, which are inherent both in pattern recognition and in the core functions of FGCS. The next generation computers will be knowledge-based systems, which form a subdomain of artificial intelligence (a1) techniques, and soa1 provides the essential link between pattern recognition domains and different application systems. No attempt is made to discuss other essential conceptual building blocks, such as software engineering, computer architecture and very large scale integration technology unless these become very relevant in the discussions of concerned topics of the paper. A section on limitations of perception, learning and knowledge for computing machines is also included.