A posteriori agreement as a quality measure for readability prediction systems

All readability research is ultimately concerned with the research question whether it is possible for a prediction system to automatically determine the level of readability of an unseen text. A significant problem for such a system is that readability might depend in part on the reader. If different readers assess the readability of texts in fundamentally different ways, there is insufficient a priori agreement to justify the correctness of a readability prediction system based on the texts assessed by those readers. We built a data set of readability assessments by expert readers. We clustered the experts into groups with greater a priori agreement and then measured for each group whether classifiers trained only on data from this group exhibited a classification bias. As this was found to be the case, the classification mechanism cannot be unproblematically generalized to a different user group

An empirical characterisation of response types in German association norms

This article presents a study to distinguish and quantify the various types of semantic associations provided by humans, to investigate their properties, and to discuss the impact that our analyses may have on NLP tasks. Specifically, we concentrate on two issues related to word properties and word relations: (1) We address the task of modelling word meaning by empirical features in data-intensive lexical semantics. Relying on large-scale corpus-based resources, we identify the contextual categories and functions that are activated by the associates and therefore contribute to the salient meaning components of individual words and across words. As a result, we discuss conceptual roles and present evidence for the usefulness of co-occurrence information in distributional descriptions. (2) We assume that semantic associates provide a means to investigate the range of semantic relations between words and contexts, and we provide insight into which types of semantic relations are treated as important or salient by the speakers of the language

Metaphor and Corpus Linguistics Metáfora e linguística de corpus

In this paper, I look at four different aspects of metaphor research from a corpus linguistic perspective, namely: (1) the lexicogrammar of metaphors, which refers to the patterning of linguistic metaphor revealed by corpus analysis; (2) metaphor probabilities, which is a facet of metaphor that emerges from frequency-based studies of metaphor; (3) dimensions of metaphor variation, or the search for systematic parameters of variation in metaphor use across different registers; and (4) automated metaphor retrieval, which relates to the development of software to help identify metaphors in corpora. I argue that these four aspects are interrelated, and that advances in one of them can drive changes in the others.<br>Neste artigo discuto quarto aspectos da pesquisa sobre metáfora do ponto de vista da linguística de corpus: (1) a lexicogramática das metáforas, que se refere aos padrões da metáfora linguística revelados pela análise de corpus; (2) probabilidades metafóricas, que é uma faceta da metáfora que emerge a partir dos estudos relacionados à freqüência de metáforas; (3) dimensões da variação de metáforas, ou a busca por parâmetros sistemáticos de variação de uso de metáfora em diferentes gêneros; e (4) captura automática de metáfora, que está relacionada ao desenvolvimento de softwares que auxiliam na identificação de metáforas em corpora. I defendo que esses quatro aspectos são interrelacionados, e que progressos em um deles podem acarretar mudanças nos outros