Grammatical abstraction and incremental syntax analysis in a language-based editor

Ergonomics is concerned with how humans interact with systems to perform tasks that achieve goals. This interaction requires thought processes that construct and manipulate mental representations of situations to enable the selection of task-oriented actions having predicted outcomes. Mental representations are, then, central to task performance and therefore ergonomics. The present review assesses the current state of knowledge regarding the nature of mental representations, focusing particularly on: (1) the vast range of existing terminology that underpins discussions about representational constructs; (2) the important role of memory in understanding mental representation; (3) the tight coupling between external and internal representations during task performance. The review concludes by proposing an integrated framework that shows how key proposals concerning mental and external representations from leading theorists can be brought together to complement one another.

For at least 25 years, the most effective way to retarget systems software has been by using machine descriptions. But “machine description” doesn’t mean what you think. A traditional machine description does contain information about the machine, but its utility is compromised in one of two ways: The description is useful only in support of a particular algorithm, such as instruction-set emulation, LR parsing, or bottom-up tree matching. Information about the machine is inextricably intertwined with information about a particular tool’s internal representation, such as a compiler’s intermediate code.

In the design of a graphics system two essential factors are always considered. These two factors are picture processing and the human interface to the computing system. The paper presents an integrated interface for display generation (IIDG). The design approach of the IIDG system relies on combining the formal grammar for identifying user actions and the grammatical description of objects into a single context-free grammar. Such grammar represents the input of an interface generator which produces IIDG by using an LR parsing method.Since IIDG is naturally machine-dependent, the grammar which describes user actions is chosen to be supported by a known hardware system. This grammar is analysed and its compatibility for implementation is pointed out. Hence is given a detailed study of a particular biomedical application to mechanise the identification of sub-median and telocentric chromosomes. The mechanisation is based on exploiting the context-free grammar to find canonical collections of the corresponding LR parser. These collections provide the states of a deterministic finite automaton and could be used to construct the parsing table which determines the syntactic structure of a choromosome.

Many computational approaches have been developed for modelling and analysing the RNA secondary structure. These approaches are based on diverse methods such as grammars, dynamic programming, matching and evolutionary algorithms. This paper proposes a new parsing algorithm for the prediction of RNA secondary structures. The proposed algorithm is based on the shift-reduce LR parsing algorithm for programming languages. It has two main contributions: it extends the LR parsing algorithm by using a Stochastic Context-Free Grammar (SCFG) instead of Context-Free Grammar (CFG) for parsing RNA secondary structures; it extends the LR parsing algorithm by using a multithreaded approach to handle the LR parsing conflicts resulting from the use of ambiguous grammars.

Constructing a mental representation from an abstract technical diagram

Given that context-free grammars (CFG) cannot adequately describe natural languages, grammar formalisms beyond CFG that are still computationally tractable are of central interest for computational linguists. This book provides an extensive overview of the formal language landscape between CFG and PTIME, moving from Tree Adjoining Grammars to Multiple Context-Free Grammars and then to Range Concatenation Grammars while explaining available parsing techniques for these formalisms. Although familiarity with the basic notions of parsing and formal languages is helpful when reading this book, it is not a strict requirement. The presentation is supported with many illustrations and examples relating to the different formalisms and algorithms, and chapter summaries, problems and solutions. The book will be useful for students and researchers in computational linguistics and in formal language theory.

Previous studies have suggested that focusing an element can enhance the activation of the focused element and bring about a number of processing benefits. However, whether and how this local prominence of information interacts with global discourse organization remains unclear. In the present study, we addressed this issue in two experiments. Readers were presented with four-sentence discourses. The first sentence of each discourse contained a critical word that was either focused or unfocused in relation to a wh-question preceding the discourse. The second sentence either maintained or shifted the topic of the first sentence. Participants were told to read for comprehension and for a probe recognition task in which the memory of the critical words was tested. In Experiment 1, when the probe words were tested immediately after the point of topic shift, we found shorter response times for the focused critical words than the unfocused ones regardless of topic manipulation. However, in Experiment 2, when the probe words were tested two sentences away from the point of topic shift, we found the facilitation effect of focus only in the topic-maintained discourses, but not in the topic-shifted discourses. This suggests that the facilitation effect of focus was not immediately suppressed at the point of topic shifting, but when additional information was added to the new topic. Our findings provide evidence for the dynamic interplay between global topic structure and local salience of information and have important implications on how activation of information fluctuates in mental representation.

Incremental Conceptualization for Language Production discusses the simultaneous actions involved in thinking and speaking, as well as the piecemeal way in which individuals construct an internal representation of the external world and use this internal representation for speaking. Author Markus Guhe presents the first computational model that captures these observations in a cognitively adequate fashion. The volume is an innovative look at the mind’s process of producing semantic representations that can be transformed into language. The first section of the book illustrates four stages of conceptualization: construction of a conceptual representation; selection of content to be verbalized; linearization of the selected content; and generation of preverbal messages. Guhe then analyzes incremental processing — processing that takes place in a piecemeal fashion — and offers a blueprint of incremental models while discussing the dimensions along which the processing principles and the blueprint varies. Finally, incremental processing and conceptualization merge to form the incremental conceptualiser model (inC). The effective use of inC is demonstrated through simulations carried out with the implementation of the model. Intended for researchers in cognitive science, particularly cognitive modeling of language, this volume will also interest researchers in artificial intelligence, computational linguistics, psycholinguistics, and linguistics and psychology.

The aim of this book is to shed light on processes associated with the construction of cognitive maps, that is to say, with the construction of internal representations of very large spatial entities such as towns, cities, neighborhoods, landscapes, metropolitan areas, environments and the like. Because of their size, such entities can never be seen in their entirety, and consequently one constructs their internal representation by means of visual, as well as non-visual, modes of sensation and information: text; auditory, haptic and olfactory means for example, or by inference. Intersensory coordination and information-transfer thus play a crucial role in the construction of cognitive maps.

Cognitive Cities: Intelligence, Environment and Space

The Generalized LR parsing algorithm for context-free grammars is notable for having a decent worst-case running time (cubic in the length of the input string, if implemented efficiently), as well as much better performance on “good” grammars. This paper extends the Generalized LR algorithm to the case of “grammars with left contexts” (M. Barash, A. Okhotin, “An extension of context-free grammars with one-sided context specifications”, Inform. Comput., 2014), which augment the context-free grammars with special operators for referring to the left context of the current substring, along with a conjunction operator (as in conjunctive grammars) for combining syntactical conditions. All usual components of the LR algorithm, such as the parsing table, shift and reduce actions, etc., are extended to handle the context operators. The resulting algorithm is applicable to any grammar with left contexts and has the same worst-case cubic-time performance as in the case of context-free grammars.

Incremental parsing has long been recognized as a technique of great utility in the construction of language‐based editors, and correspondingly, the area currently enjoys a mature theory. Unfortunately, many practical considerations have been largely overlooked in previously published algorithms. Many user requirements for an editing system necessarily impact on the design of its incremental parser, but most approaches focus only on one: response time. This paper details an incremental parser based on LR parsing techniques and designed for use in a modeless syntax recognition editor. The nature of this editor places significant demands on the structure and quality of the document representation it uses, and hence, on the parser. The strategy presented here is novel in that both the parser and the representation it constructs are tolerant of the inevitable and frequent syntax errors that arise during editing. This is achieved by a method that differs from conventional error repair techniques, and that is more appropriate for use in an interactive context. Furthermore, the parser aims to minimize disturbance to this representation, not only to ensure other system components can operate incrementally, but also to avoid unfortunate consequences for certain user‐oriented services. The algorithm is augmented with a limited form of predictive tree‐building, and a technique is presented for the determination of valid symbols for menu‐based insertion. Copyright © 2001 John Wiley & Sons, Ltd.

Tomita's parsing algorithm [Tomita 86], which adapted the LR parsing algorithm to context free grammars, makes use of a breadth-first strategy to handl LR table conflicts. As the breadth-first strategy is compatible with parallel processing, we can easily develop a parallel generalized LR parser based on Tomita's algorithm [Tanaka 89]. However, there is a problem in that this algorithm synchronizes parsing processes on each shift action for the same input word to merge many stacks into Graph Structured Stacks (GSS). In other words, a process that has completed a shift action must wait until all other processes have ended theirs --- a strategy that reduces parallel performance. We have developed a new parallel parsing algorithm that does not need to wait for shift actions before merging many stacks, using stream communication of a concurrent logic programming language called GHC [Ueda 85]. Thus we obtain a parallel generalized LR parser implemented in GHC.

Many graph analysis problems can be formulated as formal language-constrained path querying problems where the formal languages are used as constraints for navigational path queries. Recently, the context-free language (CFL) reachability formulation has become very popular and can be used in many areas, for example, querying graph databases, Resource Description Framework (RDF) analysis. However, the generative capacity of context-free grammars (CFGs) is too weak to generate some complex queries, for example, from natural languages, and the various extensions of CFGs have been proposed. Multiple context-free grammar (MCFG) is one of such extensions of CFGs. Despite the fact that, to the best of our knowledge, there is no algorithm for MCFL-reachability, this problem is known to be decidable. This paper is devoted to developing the first such algorithm for the MCFL-reachability problem. The essence of the proposed algorithm is to use a set of Boolean matrices and operations on them to find paths in a graph that satisfy the given constraints. The main operation here is Boolean matrix multiplication. As a result, the algorithm returns a set of matrices containing all information needed to solve the MCFL-reachability problem. The presented algorithm is implemented in Python using GraphBLAS API. An analysis of real RDF data and synthetic graphs for some MCFLs is performed. The study showed that using a sparse format for matrix storage and parallel computing for graphs with tens of thousands of edges the analysis time can be 10–20 minutes. The result of the analysis provides tens of millions of reachable vertex pairs. The proposed algorithm can be applied in problems of static code analysis, bioinformatics, network analysis, as well as in graph databases when a path query cannot be expressed using context-free grammars. The provided algorithm is linear algebra-based, hence, it allows one to use high-performance libraries and utilize modern parallel hardware.

A unifying model for lookahead LR parsing