| license: mit | |
| task_categories: | |
| - token-classification | |
| language: | |
| - de | |
| # CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction | |
| This inofficial dataset repository provides a CoNLL-like version of the CO-Fun NER dataset, that was proposed in the CO-Fun paper: | |
| > The process of cyber mapping gives insights in relationships among financial entities and service providers. Centered around the outsourcing practices of companies within fund prospectuses in Germany, we introduce a dataset specifically designed for named entity recognition and relation extraction tasks. The labeling process on 948 sentences was carried out by three experts which yields to 5,969 annotations for four entity types (Outsourcing, Company, Location and Software) and 4,102 relation annotations (Outsourcing-Company, Company-Location). State-of-the-art deep learning models were trained to recognize entities and extract relations showing first promising results. | |
| ## Preprocessing | |
| The notebook [Export-To-CoNLL.ipynb](Export-To-CoNLL.ipynb) performs the necessary steps to create a CoNLL-like version of the CO-Fun dataset, that could easily be used for fine-tuning NER models. | |
| Additionally, the [FlairDatasetTest.ipynb](FlairDatasetTest.ipynb) notebooks loads the dataset with the Flair dataset loader and checks, if the number of parsed sentences is correct and identical to the number of sentences reported in the official CO-Fun paper. | |
| ## Named Entites | |
| The CO-Fun dataset provides annotations for the following Named Entities: | |
| * `Auslagerung` (engl. outsourcing) | |
| * `Unternehmen` (engl. company) | |
| * `Ort` (engl. location) | |
| * `Software` | |
| # Licence | |
| The original CO-Fun dataset is released under MIT license. Thus, this preprocessed version is also licenced under MIT. |