CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction

N Foroutan, M Schröder, A Dengel - arXiv preprint arXiv:2403.15322, 2024 - arxiv.org
The process of cyber mapping gives insights in relationships among financial entities and
service providers. Centered around the outsourcing practices of companies within fund …

How's Business Going Worldwide? A Multilingual Annotated Corpus for Business Relation Extraction

H Khaldi, F Benamara, G Siegel… - 13th Conference …, 2022 - ut3-toulouseinp.hal.science
The business world has changed due to the 21 st century economy, where borders have
melted and trades became free. Nowadays, competition is no longer only at the local market …

[PDF][PDF] A closer look to your business network: Multitask relation extraction from economic and financial french content

H Khaldi, F Benamara, C Pradel… - The AAAI-22 Workshop …, 2022 - researchgate.net
Online textual content constitutes a valuable source of information for market stakeholders,
enabling them to unveil their business network's most important operations and interactions …

How can a teacher make learning from sparse data softer? application to business relation extraction

F Benamara, H Khaldi, C Pradel… - 4th Workshop on …, 2022 - hal.science
Business Relation Extraction between market entities is a challenging information extraction
task that suffers from data imbalance due to the over-representation of negative relations …

Business relation extraction from texts

H Khaldi - 2022 - theses.hal.science
The economy of the twenty-first century has shaped the economic landscape and changed
the way market stakeholders interact with one another in a global market where national …

[PDF][PDF] How's Business Going Worldwide? A Multilingual Corpus for Business Relation Extraction

K Hadjer, B Farah, P Camille, S Grégoire, AG Nathalie - f003.backblazeb2.com
Settings Models PRFPRFPRFPRF S0‡ Monolg. 67.7 71.9 69.5 72.2 66.8 69.0 74.4 72.5
73.1 75.8 73.2 74.3 S1 EN 66.8 72.4 69.1 67.8 51.9 57.3 72.2 57.3 62.3 41.6 32.4 34.8 FR …