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The Shared Task on Source and Target Extraction from Political Speeches (STEPS) first ran in 2014 and is organized by the Interest Group on German Sentiment Analysis (IGGSA). This volume presents the proceedings of the workshop of the second iteration of the shared task. The workshop was held at KONVENS 2016 at Ruhr-University Bochum on September 22, 2016.
Alternations play a central role in most current theories of verbal argument structure, wich are devides primarily to model the syntactic flexibility of verbs. Accordingly, these frameworks take verbs, and their projection properties, to be the sole contributors of thematic content to the clause. Approached from this perspective, the German applicative (or be-prefix) construction has puzzling properties. First, while many applicative verbs have transparent base forms, many, including those coined from nouns, do not. Second, applicative verbs are bound by interpretive and argument-realization conditions which cannot be traced to their base forms, if any. These facts suggest that applicative formation is not appropriately modeled as a lexical rule.
Using corpus data from a diverse array of genres, Michaelis and Ruppenhofer propose a unified solution to these two puzzles within the framework of Construction Grammar. Central to this account is the concept of valence augmentation: argument-structure constructions denote event types, and therefore license valence sets which may properly include those of their lexical fillers. As per Panini's Law, resolution of valence mismatch favors the construction over the verb. Like verbs of transfer and location, the applicative construction has a prototype-based event-structure representation: diverse implications of applicative predications--including iteration, transfer, affectedness, intensity and saturation--are shown to derive via regular patterns of semantic extension from the topological concept of coverage.
Offensive language in social media is a problem currently widely discussed. Researchers in language technology have started to work on solutions to support the classification of offensive posts. We present the pilot edition of the GermEval Shared Task on the Identification of Offensive Language. This shared task deals with the classification of German tweets from Twitter. GermEval 2018 is the fourth workshop in a series of shared tasks on German processing.
The 2014 issue of KONVENS is even more a forum for exchange: its main topic is the interaction between Computational Linguistics and Information Science, and the synergies such interaction, cooperation and integrated views can produce. This topic at the crossroads of different research traditions which deal with natural language as a container of knowledge, and with methods to extract and manage knowledge that is linguistically represented is close to the heart of many researchers at the Institut für Informationswissenschaft und Sprachtechnologie of Universität Hildesheim: it has long been one of the institute’s research topics, and it has received even more attention over the last few years. The main conference papers deal with this topic from different points of view, involving flat as well as deep representations, automatic methods targeting annotation and hybrid symbolic and statistical processing, as well as new Machine Learning-based approaches, but also the creation of language resources for both machines and humans, and methods for testing the latter to optimize their human-machine interaction properties. In line with the general topic, KONVENS-2014 focuses on areas of research which involve this cooperation of information science and computational linguistics: for example learning-based approaches, (cross-lingual) Information Retrieval, Sentiment Analysis, paraphrasing or dictionary and corpus creation, management and usability.
The 2014 issue of KONVENS is even more a forum for exchange: its main topic is the interaction between Computational Linguistics and Information Science, and the synergies such interaction, cooperation and integrated views can produce. This topic at the crossroads of different research traditions which deal with natural language as a container of knowledge, and with methods to extract and manage knowledge that is linguistically represented is close to the heart of many researchers at the Institut für Informationswissenschaft und Sprachtechnologie of Universität Hildesheim: it has long been one of the institute’s research topics, and it has received even more attention over the last few years.