Klexikon：用于联合汇总和简化的德国数据集
Klexikon: A German Dataset for Joint Summarization and Simplification
摘要：
传统上，文本简化被视为单语翻译任务，其中源文本和其简化对应物之间的句子被对齐以进行训练。然而，特别是对于较长的输入文档，摘要文本（或完全删除不相关的内容）在简化过程中起着重要作用，这在现有的数据集中目前没有反映出来。与此同时，非英语语言的资源普遍稀缺，无法培训新的解决方案。为了解决这个问题，我们提出了一个系统，可以共同总结和简化长源文件的核心要求。我们进一步描述了创建一个新的数据集的联合文本简化和总结的基础上，德国的维基百科和德国儿童的词典“Klexikon”，包括近2900个文件。我们发布了一个文档对齐的版本，特别强调了摘要方面，并提供了统计证据，表明此资源也非常适合简化。代码和数据可以在Github上找到：https://github.com/dennlinger/klexikon
英文摘要：
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
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
