Klexikon: A German Dataset for Joint Summarization and Simplification
This provides a resource for researchers working on text simplification and summarization in German, though it is incremental as it extends existing work to a new language and task combination.
The authors addressed the lack of datasets for joint summarization and simplification, especially in non-English languages, by creating Klexikon, a German dataset with almost 2900 documents based on Wikipedia and a children's lexicon, which is well-suited for simplification tasks.
Traditionally, Text Simplification is treated as a monolingual translation task where sentences between source texts and their simplified counterparts are aligned for training. However, especially for longer input documents, summarizing the text (or dropping less relevant content altogether) plays an important role in the simplification process, which is currently not reflected in existing datasets. Simultaneously, resources for non-English languages are scarce in general and prohibitive for training new solutions. To tackle this problem, we pose core requirements for a system that can jointly summarize and simplify long source documents. We further describe the creation of a new dataset for joint Text Simplification and Summarization based on German Wikipedia and the German children's lexicon "Klexikon", consisting of almost 2900 documents. We release a document-aligned version that particularly highlights the summarization aspect, and provide statistical evidence that this resource is well suited to simplification as well. Code and data are available on Github: https://github.com/dennlinger/klexikon