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Linguistic query systems are special purpose IR applications. We present a novel state-of-the-art approach for the efficient exploitation of very large linguistic corpora, combining the advantages of relational database management systems (RDBMS) with the functional MapReduce programming model. Our implementation uses the German DEREKO reference corpus with multi-layer
linguistic annotations and several types of text-specific metadata, but the proposed strategy is language-independent and adaptable to large-scale multilingual corpora.
Interested in formally modelling similarity between narratives, we investigate judgements of similarity between narratives in a small corpus of film reviews and book–film comparisons. A main finding is that judgements tend to concern multiple levels of story representation at once. As these texts are pragmatically related to reception contexts, we find many references to reception quality and optimality. We conclude that current formal models of narrative can not capture the task of naturalistic narrative comparisons given in the analysed reviews, but that the development of models containing a more reception-oriented point of view will be necessary.
The understanding of story variation, whether motivated by cultural currents or other factors, is important for applications of formal models of narrative such as story generation or story retrieval. We present the first stage of an experiment to elicit natural narrative variation data suitable for evaluation with respect to story similarity, to qualitative and quantitative analysis of story variation, and also for data processing. We also present few preliminary results from the first stage of the experiment, using Red Riding Hood and Romeo and Juliet as base texts.
The present paper provides a new approach to the form-function relation in Latin declension. First, inflections are discussed from a functional point of view with special consideration to questions of syncretism. A case hierarchy is justified for Latin that conforms to general observations on case systems. The analysis leads to a markedness scale that provides a ranking of case-number-combinations from unmarked to most marked. Systematic syncretism always applies to contiguous sections of the case-number-scale (‘syncretism fields’). Second, inflections are analysed from a formal point of view taking into account partial identities and differences among noun endings. Theme vowels being factored out, endings are classified on the basis of their make-up, e.g., as sigmatic endings; as containing desinential (non-thematic) vowels; as containing long vowels; and so on. The analysis leads to a view of endings as involving more basic elements or ‘markers’. Endings of the various declensions instantiate a small number of types, and these can be put into a ranked order (a formal scale) that applies transparadigmatically. Third, the relationship between the independently substantiated functional and formal hierarchies is examined. In any declension, the form-function-relationship is established by aligning the relevant formal and functional scales (or ‘sequences’). Some types of endings are in one-to-one correspondence with bundles of morphosyntactic properties as they should be according to a classical morphemic approach, but others are not. Nevertheless, endings can be assigned a uniform role if the form-function-relationship is understood to be based on an alignment of formal and functional sequences. A diagrammatical form-function relationship is revealed that could not be captured in classical or refined morphemic approaches.
Igel is a small XQuery-based web application for examining a collection of document grammars; in particular, for comparing related document grammars to get a better overview of their differences and similarities. In its initial form, Igel reads only DTDs and provides only simple lists of constructs in them (elements, attributes, notations, parameter entities). Our continuing work is aimed at making Igel provide more sophisticated and useful information about document grammars and building the application into a useful tool for the analysis (and the maintenance!) of families of related document grammars
In this paper, we report on an effort to develop a gold standard for the intensity ordering of subjective adjectives. Rather than pursue a complete order as produced by paying attention to the mean scores of human ratings only, we take into account to what extent assessors consistently rate pairs of adjectives relative to each other. We show that different available automatic methods for producing polar intensity scores produce results that correlate well with our gold standard, and discuss some conceptual questions surrounding the notion of polar intensity.
Freezing in it-clefts
(2013)
This paper addresses the task of finding antecedents for locally uninstantiated arguments. To resolve such null instantiations, we develop a weakly supervised approach that investigates and combines a number of linguistically motivated strategies that are inspired by work on semantic role labeling and corefence resolution. The performance of the system is competitive with the current state-of-the-art supervised system.
We examine predicative adjectives as an unsupervised criterion to extract subjective adjectives. We do not only compare this criterion with a weakly supervised extraction method but also with gradable adjectives, i.e. another highly subjective subset of adjectives that can be extracted in an unsupervised fashion. In order to prove the robustness of this extraction method, we will evaluate the extraction with the help of two different state-of-the-art sentiment lexicons (as a gold standard).
Introduction
(2013)
In the rapidly changing circumstances of our increasingly digital world, reading is also becoming an increasingly digital experience: electronic books (e-books) are now outselling print books in the United States and the United Kingdom. Nevertheless, many readers still view e-books as less readable than print books. The present study thus used combined EEG and eyetracking measures in order to test whether reading from digital media requires higher cognitive effort than reading conventional books. Young and elderly adults read short texts on three different reading devices: a paper page, an e-reader and a tablet computer and answered comprehension questions about them while their eye movements and EEG were recorded. The results of a debriefing questionnaire replicated previous findings in that participants overwhelmingly chose the paper page over the two electronic devices as their preferred reading medium. Online measures, by contrast, showed shorter mean fixation durations and lower EEG theta band voltage density – known to covary with memory encoding and retrieval – for the older adults when reading from a tablet computer in comparison to the other two devices. Young adults showed comparable fixation durations and theta activity for all three devices. Comprehension accuracy did not differ across the three media for either group. We argue that these results can be explained in terms of the better text discriminability (higher contrast) produced by the backlit display of the tablet computer. Contrast sensitivity decreases with age and degraded contrast conditions lead to longer reading times, thus supporting the conclusion that older readers may benefit particularly from the enhanced contrast of the tablet. Our findings thus indicate that people’s subjective evaluation of digital reading media must be dissociated from the cognitive and neural effort expended in online information processing while reading from such devices.
A tale of many stories: explaining policy diffusion between European higher education systems
(2013)
The thesis ”A Tale of Many Stories - Explaining Policy Diffusion between European Higher Education Systems" systematically examines diffusion processes and their effects with regard to a rather neglected policy area – the case of European higher education policy. The thesis contributes to the slowly growing number of comparative and mechanism-based studies on policy diffusion and represents the first study on the diffusion of policies between European Higher Education Systems. The main aim is to contrast and compare testable and coherent explanatory models on the functioning of different diffusion mechanisms. Three sets of explanatory models on the relationship between variables triggering and conditioning diffusion mechanisms and their impact on policy adoption are drawn from mechanism-based thinking on policy diffusion: on learning, socialization, and externalities. These approaches conceptualize the policy process in terms of interdependencies between international and national actors. Explanatory models based on assumptions about domestic policies and the common responses of countries to similar policy problems extend this theoretical framework. The thesis is based on event history modelling of policy change and adoption in higher education systems of 16 West European countries between the yeas 1980 and 1998. Overall 14 policy items describing performance-orientated reforms for public universities ranging from the adoption of external quality assurance systems to tuition fees are examined. Empirically, the main research question is what international, national and policy-specific factors cause and condition diffusion processes and the adoption of public policies? Evidence can be found for and against all of the four theoretical approaches tested. In comparison, many of the assumptions related to interdependencies lack robustness, whereas the common response model is the most stable one. This does not mean that explanatory models based on interdependent decision-making are not suitable for analysing policy diffusion in higher education. Rather interdependency is a multi- dimensional concept that requires a comparative assessment of diffusion mechanisms. Some of explanatory factors based on interdependent decision- making are still supported by the empirical analysis though. From this point of view, the recommendation for analysing diffusion is to start with a model based on domestic politics, that is successively extended by explanatory factors dealing with interdependencies between international and national actors. Diffusion variables matter – but it is only one side of the tale on policy diffusion.
We investigate the task of detecting reliable statements about food-health relationships from natural language texts. For that purpose, we created a specially annotated web corpus from forum entries discussing the healthiness of certain food items. We examine a set of task-specific features (mostly) based on linguistic insights that are instrumental in finding utterances that are commonly perceived as reliable. These features are incorporated in a supervised classifier and compared against standard features that are widely used for various tasks in natural language processing, such as bag of words, part-of speech and syntactic parse information.