Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout

Understand

State-of-the-art solutions for Natural Language Processing (NLP) are able to capture a broad range of contexts, like the sentence-level context or document-level context for short documents.

• But these solutions are still struggling when it comes to longer, real-world documents with the information encoded in the spatial structure of the document, such as page elements like tables, forms, headers, openings or footers; complex page layout or presence of multiple pages.
• To encourage progress on deeper and more complex Information Extraction (IE) we introduce a new task (named Kleister) with two new datasets.
• Utilizing both textual and structural layout features, an NLP system must find the most important information, about various types of entities, in long formal documents.