Current Projects

Current Projects

Experimental software from the research projects of UKP can be found at GitHub: https://github.com/ukplab

German Research Foundation (DFG)

Evidence

Dictionaries are an essential resource in many domains of research, education, and natural language processing (NLP). One crucial part of dictionaries are example sentences which illustrate real-world use cases of a lemma. However, finding good example sentences in large corpora imposes a heavy workload on lexicographers. In this project, we develop a novel system which eases the work of lexicographers by interactively assessing the goodness and diversity of dictionary examples.

INCEpTION: Towards an Infrastructure for the Distributed Exploration and Annotation of Large Corpora and Knowledge Bases

The annotation of specific semantic phenomena often require compiling task-specific corpora and creating or extending task-specific knowledge bases. Presently, researchers require a broad range of skills and tools to address such semantic annotation tasks. INCEpTION aims towards building an annotation platform that incorporates corpus extraction, annotation, and knowledge management into a joint platform.

Informatik selbstgemacht! (computer science self-made!)

Funded by AIPHES, this workshop for pupils in 6th/7th grade promotes women in STEM. Lead by female computer science students from TU Darmstadt, the pupils gain some data analytics and programming skills.

Information Consolidation: A New Paradigm in Knowledge Search (DIP project)

The DIP project – an international cooperation with Bar-Ilan University and Israel Institute of Technology – aims at the next big step in information access technology. The goal is to support users in identifying and assimilating the large set of relevant statements found within multitudes of documents which are usually retrieved by the current search technologies. Novel methods for statement extraction, information consolidation, and inferring relations represent the core research areas within this project.

Research Training Group AIPHES (“Adaptive Information Preparation from Heterogeneous Sources”), DFG GRK 1994

AIPHES develops new methods to deal with information overload by summarizing multiple documents to a condensed summary. We develop adaptive methods to create summaries of any type from multiple sources and across different genres. To do so, we combine different methodological backgrounds – computational linguistics, computer science, machine learning – to approach the task of extracting, summarizing and evaluating textual information from different sources.

Open Argument Mining

This project aims at investigating computational methods that continuously improve their capability to recognize arguments in ongoing debates, align incomplete arguments with previous arguments and enrich them with automatically acquired background knowledge, and constantly extend semantic knowledge bases with information required to understand arguments.

Federal Ministry of Education and Research (BMBF)

Decision Support by Means of Automatically Extracting Natural Language Arguments from Big Data

In order to make informed decisions, appropriate arguments are needed. However, the mere amount of information and the complexity of many questions frequently prevents us from finding all arguments that are relevant for a reasonable decision. Within the “Decision support by means of automatically extracting natural language arguments from big data” (ArgumenText) project, the UKP Lab develops novel Argument Mining methods for extracting arguments from large and heterogeneous text sources in order to facilitate decision making processes. In response to a user-defined search query, neural networks determine relevant arguments in realtime and summarize them in a comprehensive way. In contrast to conventional systems, an argumentative information system can show the reasons for or against a decision.

Software Campus (BMBF)

Software Campus program is funded by Germany's Federal Ministry for Education and Research (BMBF).

In close collaboration with strong partners from industry and research, Software Campus participants develop innovative academic IT projects and benefit from an individually tailored training curriculum with outstanding academics and managers. The Federal Ministry of Education and Research (BMBF) provides funding of up to EUR 100,000 for each IT project.

UKP Lab is currently represented in the network by the following researchers:

The projects already finished within the scope of the program: