The potential of Swetra — A multilanguage MT system

One may indicate the potentials of an MT system by stating what text genres it can process, e.g., weather reports and technical manuals. This approach is practical, but misleading, unless domain knowledge is highly integrated in the system. Another way to indicate which fragments of language the system can process is to state its grammatical potentials, or more formally, which languages the grammars of the system can generate. This approach is more technical and less understandable to the layman (customer), but it is less misleading, since it stresses the point that the fragments which can be translated by the grammars of a system need not necessarily coincide exactly with any particular genre. Generally, the syntactic and lexical rules of an MT system allow it to translate many sentences other than those belonging to a certain genre. On the other hand it probably cannot translate all the sentences of a particular genre. Swetra is a multilanguage MT system defined by the potentials of a formal grammar (standard referent grammar) and not by reference to a genre. Successful translation of sentences can be guaranteed if they are within a specified syntactic format based on a specified lexicon. The paper discusses the consequences of this approach (Grammatically Restricted Machine Translation, GRMT) and describes the limits set by a standard choice of grammatical rules for sentences and clauses, noun phrases, verb phrases, sentence adverbials, etc. Such rules have been set up for English, Swedish and Russian, mainly on the basis of familiarity (frequency) and computer efficiency, but restricting the grammar and making it suitable for several languages poses many problems for optimization. Sample texts — newspaper reports — illustrate the type of text that can be translated with reasonable success among Russian, English and Swedish.     

The potential of swetra—A multilanguage MT system

One may indicate the potentials of an MT system by stating what text genres it can process, e.g., weather reports and technical manuals. This approach is practical, but misleading, unless domain knowledge is highly integrated in the system. Another way to indicate which fragments of language the system can process is to state its grammatical potentials, or more formally, which languages the grammars of the system can generate. This approach is more technical and less understandable to the layman (customer), but it is less misleading, since it stresses the point that the fragments which can be translated by the grammars of a system need not necessarily coincide exactly with any particular genre. Generally, the syntactic and lexical rules of an MT system allow it to translate many sentences other than those belonging to a certain genre. On the other hand it probably cannot translate all the sentences of a particular genre. Swetra is a multilanguage MT system defined by the potentials of a formal grammar (standard referent grammar) and not by reference to a genre. Successful translation of sentences can be guaranteed if they are within a specified syntactic format based on a specified lexicon. The paper discusses the consequences of this approach (Grammatically Restricted Machine Translation, GRMT) and describes the limits set by a standard choice of grammatical rules for sentences and clauses, noun phrases, verb phrases, sentence adverbials, etc. Such rules have been set up for English, Swedish and Russian, mainly on the basis of familiarity (frequency) and computer efficiency, but restricting the grammar and making it suitable for several languages poses many problems for optimization. Sample texts—newspaper reports—illustrate the type of text that can be translated with reasonable success among Russian, English and Swedish.     

A survey of grammatical inference in software engineering

Grammatical inference – used successfully in a variety of fields such as pattern recognition, computational biology and natural language processing – is the process of automatically inferring a grammar by examining the sentences of an unknown language. Software engineering can also benefit from grammatical inference. Unlike these other fields, which use grammars as a convenient tool to model naturally occurring patterns, software engineering treats grammars as first-class objects typically created and maintained for a specific purpose by human designers. We introduce the theory of grammatical inference and review the state of the art as it relates to software engineering.     

汉语词汇测试自动命题研究

为了提升汉语词汇测试的命题效率,该文从汉语语言特性和二语教学需求出发,对词语听力、多空词语选择、词语排序和单空词语选择四种词汇测试题型进行自动命题尝试,以满足不同语言信息、不同难度的词汇知识考查。在词语特征的提取上,构建了一个覆盖词音、词形、词义、语法、搭配、偏误各层次信息的词汇知识库,在句子特征的提取上,实现了语法项目自动识别、句子难度分析等算法,为自动命题中的题干句、目标词和干扰项选择提供依据。通过词句选择和语块合成等步骤,生成四种题型共计7 263道词汇测试题。人工测试数据显示,词汇测试自动命题的初步尝试取得了较好的效果,约58%的试题被评价为完全合理,经人工简单调整,试题接受率达到75.7%。     

Horn逻辑程序和形式文法之间的对应关系

The paper researches Horn logic programs with grammatical view. The correspondence between Horn logic programs and grammars is found. The method by which type-0 grammars generate the least Herbrand models of logic programs is found. The method by which Horn logic programs generate the languages of type-0 grammars is found.The characterization of Horn Logic programs that are semantically equavanent to type-2 grammars and type-3 grammars is found.     

A comparison of grammatical genetic programming grammars for controlling femtocell network coverage

We study grammars used in grammatical genetic programming (GP) which create algorithms that control the base station pilot power in a femtocell network. The overall goal of evolving algorithms for femtocells is to create a continuous online evolution of the femtocell pilot power control algorithm in order to optimize their coverage. We compare the performance of different grammars and analyse the femtocell simulation model using the grammatical genetic programming method called grammatical evolution. The grammars consist of conditional statements or mathematical functions as are used in symbolic regression applications of GP, as well as a hybrid containing both kinds of statements. To benchmark and gain further information about our femtocell network simulation model we also perform random sampling and limited enumeration of femtocell pilot power settings. The symbolic regression based grammars require the most configuration of the evolutionary algorithm and more fitness evaluations, whereas the conditional statement grammar requires more domain knowledge to set the parameters. The content of the resulting femtocell algorithms shows that the evolutionary computation (EC) methods are exploiting the assumptions in the model. The ability of EC to exploit bias in both the fitness function and the underlying model is vital for identifying the current system and improves the model and the EC method. Finally, the results show that the best fitness and engineering performances for the grammars are similar over both test and training scenarios. In addition, the evolved solutions’ performance is superior to those designed by humans.     

Parsing nonlinear languages

The diagrammatic approach to user interfaces for computer-aided software development toolkits, visual query systems, and visual programming environments, is based on the use of diagrams and charts traditionally drawn on paper. In particular, the VLG system (Visual Language Generator) has been proposed to generate icon-oriented visual languages customized for given applications. The syntactical model underlying the interpretation of a visual language in VLG has been designed to describe icon-oriented visual languages. In order to enable the VLG system to apply to any kind of graphical languages, like diagrammatic ones, it is necessary to find a more general syntactical model able to support both their generation and interpretation. This paper addresses the comprehension of the features that a grammatical formalism for nonlinear languages must have to match any requirement for an efficient parsing. To this aim, relation grammars support an easy implementation of a general parsing algorithm for multidimensional languages, parametric with respect to the rewriting rules of the grammar. We compare the expressive power of relation grammars to grammatical formalisms for graph grammars     

An observation on suffix redundancy in LL(1) error repair

We give a simple grammatical characterization of the notion of suffix redundancy presented procedurally in a recent article by Fischer and Mauney. It is shown that certain properties of grammars related to suffix redundancy can be decided at parser generation time. Some suggestions concerning efficiency of repair attempts conclude the article.     

An observation on suffix redundancy in LL(1) error repair

We give a simple grammatical characterization of the notion of suffix redundancy presented procedurally in a recent article by Fischer and Mauney. It is shown that certain properties of grammars related to suffix redundancy can be decided at parser generation time. Some suggestions concerning efficiency of repair attempts conclude the article.     

Remarks on some aspects of language structure and their relevance to pattern analysis

Some specific aspects of language structure are examined in detail in the context of pattern analysis. In particular, a transformational grammar is constructed for a class of patterns, following the linguistic formulation very closely, by taking a simple example and working it out in detail. Many of the characteristics of the transformational grammars of linguists show up even in this simple example. The need for looking for grammars of different styles and the problem of making meaningful assignment of probabilities to sentences in the context of transformational grammars have also been briefly discussed.     

A Toolkit for Generating Sentences from Context-Free Grammars

Producing sentences from a grammar, according to various criteria, is required in many applications. It is also a basic building block for grammar engineering. This paper presents a toolkit for context-free grammars, which mainly consists of several algorithms for sentence generation or enumeration and for coverage analysis for context-free grammars. The toolkit deals with general context-free grammars. Besides providing implementations of algorithms, the toolkit also provides a simple graphical user interface, through which the user can use the toolkit directly. The toolkit is implemented in Java and is available at http://lcs.ios.ac.cn/~zhiwu/toolkit.php. In the paper, the overview of the toolkit and the major algorithms implemented in the toolkit are presented, and experimental results and preliminary applications of the toolkit are also contained.     

LEFT TO RIGHT PARSING OF LEXICALIZED TREE-ADJOINING GRAMMARS1

This paper presents an algorithm (a parser) for analyzing sentences according to grammatical constraints expressed in the framework of lexicalized tree-adjoining grammar. For the current grammars of English, the algorithm behaves much better and requires much less time than its worst-case complexity. The main objective of this work is to design a practical parser whose average-case complexity is much superior to its worst case. Most of the previous methods always required the worst-case complexity. The algorithm can be used in two modes. As a recognizer it outputs whether the input sentence is grammatically correct or not. As a parser it outputs a detailed analysis of the grammatically correct sentences. As sentences are read from left to right, information about possible continuations of the sentence is computed. In this sense, the algorithm is called a predictive left to right parser. This feature reduces the average time required to process a given sentence. In the worst case, the parser requires an amount of time proportional to G²n⁶ for a sentence of n words and for a lexicalized tree-adjoining grammar of size G. The worst-case complexity is only reached with pathological (not naturally occurring) grammars and inputs.     

一种特殊的上下文无关文法及其语法分析

SAQ系统是一个进行软件规约获取、检验和复用的实验系统，其中以上下文无关文法表示的概念是规约的一部分.SAQ要求将概念的词法和句法定义结合在一个上下文无关文法中.如果用常规的上下文无关文法描述诸如程序设计语言和自然语言等一些复杂概念的语法，则需要把诸如空格和回车等没有实质意义的分隔符包含到语法中去(这种描述方法称为朴素表示法),使得语法描述很累赘.为此，作者设计了一种特殊的上下文无关文法,它把通常上下文无关文法定义中的非终极符集合和终极符集合进行细化.用这种文法可以相对简洁地描述程序语言和自然语言等复杂概     

Generation of text from logical formulae

The paper addresses the problem of generating sentences from logical formulae. It describes a simple and efficient algorithm for generating text which has been developed for use in machine translation, but will have wider application in natural language processing. An important property of the algorithm is that the logical form used to generate a sentence need not be one which could have been produced by parsing the sentence: formal equivalence between logical forms is allowed for. This is necessary for a machine translation system, such as the one envisaged in this paper, which uses single declarative grammars of individual languages, and declarative statements of translation equivalences for transfer. In such a system, it cannot be guaranteed that transfer will produce a logical form in the same order as would have been produced by parsing some target-language sentence, and it is not practicable to define a normal form for the logical forms. The algorithm is demonstrated using a categorial grammar and a simple indexed logic, as this allows a particularly clear and elegant formulation. It is shown that the algorithm can be adapted to phrase-structure grammars, and to more complex semantic representations than that used here.     

Grammatical inference in bioinformatics

Bioinformatics is an active research area aimed at developing intelligent systems for analyses of molecular biology. Many methods based on formal language theory, statistical theory, and learning theory have been developed for modeling and analyzing biological sequences such as DNA, RNA, and proteins. Especially, grammatical inference methods are expected to find some grammatical structures hidden in biological sequences. In this article, we give an overview of a series of our grammatical approaches to biological sequence analyses and related researches and focus on learning stochastic grammars from biological sequences and predicting their functions based on learned stochastic grammars.     

String and graph grammar characterizations of bounded regular languages

Two grammatical characterizations of the bounded regular languages are presented: one in terms of graph grammars, the other using string grammars. First it is shown that a class of state graphs recognizing the bounded regular languages can be generated by a particular second-order contextfree graph grammar. Next we call uniquely recursive a right-linear (string) grammar having at most one right-recursive production for each of its nonterminals. It is then established that the class of languages generated by uniquely recursive, sequential right-linear grammars is exactly the bounded regular languages. Some comments on the relationship between string and graph grammars are made.