|
--- |
|
task_categories: |
|
- token-classification |
|
language: |
|
- uk |
|
tags: |
|
- legal |
|
pretty_name: uk NER contracts |
|
--- |
|
|
|
### Dataset Description |
|
|
|
Legal Contracts Dataset for Training SpaCy NER Model |
|
This repository contains a specially curated dataset consisting of legal contracts. It is designed for the purpose of training a Named Entity Recognition (NER) model using SpaCy, with the aim to recognize and classify four types of entities in the text: |
|
|
|
Contract Type, |
|
Clause Title, |
|
Clause Number, |
|
Definition Title |
|
|
|
|
|
The dataset includes a broad variety of legal contracts, covering diverse domains such as employment, real estate, services, sale, lease, etc. |
|
|
|
Entities in the text have been manually labeled by experts in the field, ensuring high-quality training data for the model. |
|
|
|
Each document in the dataset has been annotated in the following format: |
|
|
|
(Start_Position, End_Position, Entity_Label) |
|
|
|
For example, a clause title may be annotated as follows: (102, 115, 'clause title') |
|
|
|
This will assist the NER model in identifying not only the text of the entity, but also its position within the document. |
|
|
|
Usage Guidelines |
|
The dataset can be loaded into a SpaCy pipeline for training a NER model. For more information on how to train a NER model using SpaCy, please refer to the SpaCy documentation. |
|
|
