This article introduces a text extension to the UN General Assembly Sponsorship Dataset. It consists of a corpus with the full text of draft resolutions presented by member states from 2000 to 2020, which allows conducting content and text-as-data analyses of over 7000 L-documents (or 5000 draft resolutions). We demonstrate the utility of the new data via applications that map the salience of topics, measure sentiment, and identify the effects of changes to the text between revisions on attracting new sponsors. The article concludes by discussing potential uses of the data in future research.