Collens
Collens is a dynamic web-based tool designed for scholars to compare textual variants with annotations. Utilizing machine learning, it offers an efficient workflow for analyzing multiple versions of literary and scholarly documents.
An Artificial Intelligence Approach to Comparing Text Versions
Literary works are dynamic entities: they go through different stages of development before publication, and often continue to change even after their first publication. The early versions of a work, such as notes, draft manuscripts and typescripts, still show the traces of this dynamic development in the form of deletions, additions or substitutions. Today, these documents are carefully transcribed, annotated and encoded in a machine-readable language. Using text comparison tools, scholars can automatically compare the encoded text versions and examine the different stages in the work’s development. So far, however, it is not possible to include the annotations in the comparison process. This means that relevant scholarly information is lost.
The project initially began investigating the use of additional annotations in Machine Learning to predict and compare textual variation. However, during the course of the project, the direction shifted towards the development of a visualisation tool and information management best practices for representing and analysing textual variation including the additional encoded annotations.
I think it’s safe to say that this is one of the prettiest visualizations the field has seen
Multilingual and Multipurpose Entity Linking Toolkit
Collens is a dynamic web-based tool designed for scholars to compare textual variants with annotations. Utilizing machine learning, it offers an efficient workflow for analyzing multiple versions of literary and scholarly documents.
Making harmonisation simple. Social scientists often have to compare items from different questionnaires or datasets. Harmony is a tool that uses natural language processing and generative AI models to help researchers harmonise questionnaire items quickly, even in different languages.