activity
20212024
most citedMulti-Attribute Relation Extraction (MARE) -- Simplifying the Application of Relation Extraction

3 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 1 cited

Scoping Review of Active Learning Strategies and their Evaluation Environments for Entity Recognition Tasks

Philipp Kohl, Yoka Krämer, Claudia Fohry +1

We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows: Ob…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2021★ 3 cited

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…

cs.CL2021★ 1 cited

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…