A New Statistical Parser Based on Bigram Lexical Dependencies

This paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. Standard bigram probability estimation techniques are extended to calculate probabilities of dependencies between pairs of words. Tests using Wall Street Journal data show that the method performs at least as well as SPATTER (Magerman 95, Jelinek et al 94), which has the best published results for a statistical parser on this task. The simplicity of the approach means the model trains on 40,000 sentences in under 15 minutes. With a beam search strategy parsing speed can be improved to over 200 sentences a minute with negligible loss in accuracy.Comment: 8 pages, to appear in Proceedings of ACL 96. Uuencoded gz-compressed postscript file created by csh script uufile

Type-driven semantic interpretation and feature dependencies in R-LFG

Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple et. al., it is natural to ask whether these make any existing components of LFG redundant. As Dalrymple and her colleagues note, LFG's f-structure completeness and coherence constraints fall out as a by-product of the linear logic machinery they propose for semantic interpretation, thus making those f-structure mechanisms redundant. Given that linear logic machinery or something like it is independently needed for semantic interpretation, it seems reasonable to explore the extent to which it is capable of handling feature structure constraints as well. R-LFG represents the extreme position that all linguistically required feature structure dependencies can be captured by the resource-accounting machinery of a linear or similiar logic independently needed for semantic interpretation, making LFG's unification machinery redundant. The goal is to show that LFG linguistic analyses can be expressed as clearly and perspicuously using the smaller set of mechanisms of R-LFG as they can using the much larger set of unification-based mechanisms in LFG: if this is the case then we will have shown that positing these extra f-structure mechanisms is not linguistically warranted.Comment: 30 pages, to appear in the the ``Glue Language'' volume edited by Dalrymple, uses tree-dvips, ipa, epic, eepic, fullnam

Architecture-based Qualitative Risk Analysis for Availability of IT Infrastructures

An IT risk assessment must deliver the best possible quality of results in a time-effective way. Organisations are used to customise the general-purpose standard risk assessment methods in a way that can satisfy their requirements. In this paper we present the QualTD Model and method, which is meant to be employed together with standard risk assessment methods for the qualitative assessment of availability risks of IT architectures, or parts of them. The QualTD Model is based on our previous quantitative model, but geared to industrial practice since it does not require quantitative data which is often too costly to acquire. We validate the model and method in a real-world case by performing a risk assessment on the authentication and authorisation system of a large multinational company and by evaluating the results w.r.t. the goals of the stakeholders of the system. We also perform a review of the most popular standard risk assessment methods and an analysis of which one can be actually integrated with our QualTD Model

Traceability for Model Driven, Software Product Line Engineering

Traceability is an important challenge for software organizations. This is true for traditional software development and even more so in new approaches that introduce more variety of artefacts such as Model Driven development or Software Product Lines. In this paper we look at some aspect of the interaction of Traceability, Model Driven development and Software Product Line

Cognitive constraints and island effects

Competence-based theories of island effects play a central role in generative grammar, yet the graded nature of many syntactic islands has never been properly accounted for. Categorical syntactic accounts of island effects have persisted in spite of a wealth of data suggesting that island effects are not categorical in nature and that nonstructural manipulations that leave island structures intact can radically alter judgments of island violations. We argue here, building on work by Paul Deane, Robert Kluender, and others, that processing factors have the potential to account for this otherwise unexplained variation in acceptability judgments. We report the results of self-paced reading experiments and controlled acceptability studies that explore the relationship between processing costs and judgments of acceptability. In each of the three self-paced reading studies, the data indicate that the processing cost of different types of island violations can be significantly reduced to a degree comparable to that of nonisland filler-gap constructions by manipulating a single nonstructural factor. Moreover, this reduction in processing cost is accompanied by significant improvements in acceptability. This evidence favors the hypothesis that island-violating constructions involve numerous processing pressures that aggregate to drive processing difficulty above a threshold, resulting in unacceptability. We examine the implications of these findings for the grammar of filler-gap dependencies