3 citations · 6 across the 4 of their papers we have counts for
4 papers · 1 filter
Explaining Relation Classification Models with Semantic Extents
Lars Klöser, Andre Büsgen, Philipp Kohl +2
In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relati…
ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP
Philipp Kohl, Nils Freyer, Yoka Krämer +5
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate t…
Multi-Attribute Relation Extraction (MARE) -- Simplifying the Application of Relation Extraction
Lars Klöser, Philipp Kohl, Bodo Kraft +1
Natural language understanding's relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Cu…
STAMP 4 NLP -- An Agile Framework for Rapid Quality-Driven NLP Applications Development
Philipp Kohl, Oliver Schmidts, Lars Klöser +3
The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data an…