Daniel Braun


2020

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MucLex: A German Lexicon for Surface Realisation
Kira Klimt | Daniel Braun | Daniela Schneider | Florian Matthes
Proceedings of the 12th Language Resources and Evaluation Conference

Language resources for languages other than English are often scarce. Rule-based surface realisers need elaborate lexica in order to be able to generate correct language, especially in languages like German, which include many irregular word forms. In this paper, we present MucLex, a German lexicon for the Natural Language Generation task of surface realisation, based on the crowd-sourced online lexicon Wiktionary. MucLex contains more than 100,000 lemmata and more than 670,000 different word forms in a well-structured XML file and is available under the Creative Commons BY-SA 3.0 license.

2019

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SimpleNLG-DE: Adapting SimpleNLG 4 to German
Daniel Braun | Kira Klimt | Daniela Schneider | Florian Matthes
Proceedings of the 12th International Conference on Natural Language Generation

SimpleNLG is a popular open source surface realiser for the English language. For German, however, the availability of open source and non-domain specific realisers is sparse, partly due to the complexity of the German language. In this paper, we present SimpleNLG-DE, an adaption of SimpleNLG to German. We discuss which parts of the German language have been implemented and how we evaluated our implementation using the TIGER Corpus and newly created data-sets.

2017

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SaToS: Assessing and Summarising Terms of Services from German Webshops
Daniel Braun | Elena Scepankova | Patrick Holl | Florian Matthes
Proceedings of the 10th International Conference on Natural Language Generation

Every time we buy something online, we are confronted with Terms of Services. However, only a few people actually read these terms, before accepting them, often to their disadvantage. In this paper, we present the SaToS browser plugin which summarises and simplifies Terms of Services from German webshops.

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Evaluating Natural Language Understanding Services for Conversational Question Answering Systems
Daniel Braun | Adrian Hernandez Mendez | Florian Matthes | Manfred Langen
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

Conversational interfaces recently gained a lot of attention. One of the reasons for the current hype is the fact that chatbots (one particularly popular form of conversational interfaces) nowadays can be created without any programming knowledge, thanks to different toolkits and so-called Natural Language Understanding (NLU) services. While these NLU services are already widely used in both, industry and science, so far, they have not been analysed systematically. In this paper, we present a method to evaluate the classification performance of NLU services. Moreover, we present two new corpora, one consisting of annotated questions and one consisting of annotated questions with the corresponding answers. Based on these corpora, we conduct an evaluation of some of the most popular NLU services. Thereby we want to enable both, researchers and companies to make more educated decisions about which service they should use.

2015

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Creating Textual Driver Feedback from Telemetric Data
Daniel Braun | Ehud Reiter | Advaith Siddharthan
Proceedings of the 15th European Workshop on Natural Language Generation (ENLG)