activity
20222026
most citedAIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First -- Using Relation Extraction to Identify Entities

1 citations · 3 across the 10 of their papers we have counts for

collaborators
Showing 2022Show all

2 papers · 1 filter

cs.CL2022★ 1 cited

Few-Shot Document-Level Relation Extraction

Nicholas Popovic, Michael Färber

We present FREDo, a few-shot document-level relation extraction (FSDLRE) benchmark. As opposed to existing benchmarks which are built on sentence-level relation extraction corpora,…

cs.CL2022★ 1 cited

AIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First -- Using Relation Extraction to Identify Entities

Nicholas Popovic, Walter Laurito, Michael Färber

In this paper, we present an end-to-end joint entity and relation extraction approach based on transformer-based language models. We apply the model to the task of linking mathemat…