University of Hildesheim
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Adapting Data Mining for German Named Entity Recognition
No full textIn the latest decades, machine learning approaches have been intensively experimented for natural language processing. Most of the time, systems rely on using statistics within the system, by analyzing texts at the token level and, for labelling tasks, categorizing each among possible classes. One may notice that previous symbolic approaches (e.g. transducers) where designed to delimit pieces of text. Our research team developped mXS, a system that aims at combining both approaches. It locates boundaries of entities by using sequential pattern mining and machine learning. This system, intially developped for French, has been adapted to German
A Hybrid Entity-Mention Pronoun Resolution Model for German Using Markov Logic Networks
No full textThis paper presents a hybrid pronoun resolution system for German. It uses a simple rule-driven entity-mention formalism to incrementally process discourse entities. Antecedent selection is performed based on Markov Logic Networks (MLNs). The hybrid architecture yields a cheap problem formulation in the MLNs w.r.t. inference complexity but pertains their expressiveness. We compare the system to a rule-driven baseline and an extension which uses a memory-based learner. We find that the MLN hybrid outperforms its competitors by large margins
WebNLP – An Integrated Web-Interface for Python NLTK and Voyant
No full textWe present WebNLP, a web-based tool that combines natural language processing (NLP) functionality from Python NLTK and text visualizations from Voyant in an integrated interface. Language data can be uploaded via the website. The results of the processed data are displayed as plain text, XML markup, or Voyant visualizations in the same website. WebNLP aims at facilitating the usage of NLP tools for users without technical skills and experience with command line interfaces. It also makes up for the shortcomings of the popular text analysis tool Voyant, which, up to this point, is lacking basic NLP features such as lemmatization or POS tagging
Mapping German Tweets to Geographic Regions
No full textWe present a first attempt at classifying German tweets by region using only the text of the tweets. German Twitter users are largely unwilling to share geolocation data. Here, we introduce a two-step process. First, we identify regionally salient tweets by comparing them to an "average" German tweet based on lexical features. Then, regionally salient tweets are assigned to one of 7 dialectal regions. We achieve an accuracy (on regional tweets) of up to 50% on a balanced corpus, much improved from the baseline. Finally, we show several directions in which this work can be extended and improved
Workshop proceedings of the 12th edition of the KONVENS conference
No full textThe workshops hosted at this iteration of KONVENS also reflect the interaction of, and common themes shared between, Computational Linguistics and Information Science: a focus on on evaluation, represented by shared tasks on Named Entity Recognition (GermEval) and on Sentiment Analysis (GESTALT); a growing interest in the processing of non-canonical text such as that found in social media (NLP4CMC) or patent documents (IPaMin); multi-disciplinary research which combines Information Science, Computer Aided Language Learning, Natural Language Processing, and E-Lexicography with the objective of creating language learning and training systems that provide intelligent feedback based on rich knowledge (ISCALPEL)
Proceedings of the 12th edition of the KONVENS conference
No full textThe 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 a 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 workshops hosted at this iteration of KONVENS also reflect the interaction of, and common themes shared between, Computational Linguistics and Information Science: a focus on on evaluation, represented by shared tasks on Named Entity Recognition (GermEval) and on Sentiment Analysis (GESTALT); a growing interest in the processing of non-canonical text such as that found in social media (NLP4CMC) or patent documents (IPaMin); multi-disciplinary research which combines Information Science, Computer Aided Language Learning, Natural Language Processing, and E-Lexicography with the objective of creating language learning and training systems that provide intelligent feedback based on rich knowledge (ISCALPEL)
German Perception Verbs: Automatic Classification of Prototypical and Multiple Non-literal Meanings
No full textThis paper presents a token-based automatic classification of German perception verbs into literal vs. multiple non-literal senses. Based on a corpus-based dataset of German perception verbs and their systematic meaning shifts, we identify one verb of each of the four perception classes optical, acoustic, olfactory, haptic, and use Decision Trees relying on syntactic and semantic corpus-based features to classify the verb uses into 3-4 senses each. Our classifier reaches accuracies between 45.5% and 69.4%, in comparison to baselines between 27.5% and 39.0%. In three out of four cases analyzed our classifier’s accuracy is significantly higher than the according baseline
NERU: Named Entity Recognition for German
No full textIn this paper, we present our Named Entity Recognition (NER) system for German – NERU (Named Entity Rules), which heavily relies on handcrafted rules as well as information gained from a cascade of existing external NER tools. The system combines large gazetteer lists, information obtained by comparison of different automatic translations and POS taggers. With NERU, we were able to achieve a score of 73.26% on the development set provided by the GermEval 2014 Named Entity Recognition Shared Task for German
Relational Work and the Display of Multilingualism in Two Facebook Groups
No full textIn this paper the authors explore the research interface between politeness theory and identity constructions within interpersonal pragmatics
Amateur theatre in Lower Saxony. A study on the conditions and procedures of amateur theaters.
No full textIn zahlreichen Städten und Gemeinden in Niedersachsen wird Theater gespielt. Die Mitglieder dieser Amateurtheater wählen gemeinsam Stücke aus, proben regelmäßig nach Feierabend, bauen selbst das Bühnenbild, schneidern die Kostüme und führen schließlich mit vielen Helfern in Dorfgemeinschaftshäusern oder Gaststätten ihre überwiegend heiteren Stücke auf. Im Publikum sitzen vor allem Menschen aus dem gleichen Ort oder der näheren Umgebung. Nach dem Kulturmonitoring Niedersachsen praktizieren 9 % der Bevölkerung in Niedersachsen ‚Theater spielen‘ als künstlerisch-kreative Freizeitbeschäftigung. Obgleich die Theaterlandschaft in Niedersachsen – und vermutlich auch in den anderen Bundesländern – sehr stark von dieser Art des Theaters geprägt ist, existieren kaum wissenschaftliche Erkenntnisse darüber, in welchen Strukturen Amateurtheater stattfindet und wie sich dieses weiterentwickeln kann. Auch sind Amateurtheater nur selten Gegenstand kulturpolitischer Diskussionen. Erstmalig wurden mit dieser Studie systematisch und landesweit empirisch repräsentative Daten zu Strukturen, Theaterarbeit, finanzieller Situation und zukünftigen Herausforderungen von Amateurtheatern erhoben