The first post-WWII years in Greece were devastating. After a brutal Nazi occupation, the Greek Civil War (1946–1949) erupted. It wrecked the economy and the country’s infrastructure and altered politics and the social fabric for decades to come. For the tense and unstable first years of the conflict (1946–1947), a study of the issues discussed in the Greek parliament could facilitate our understanding of the society at the time. An obstacle is that parliament proceedings are publicly available in a machine-readable form from 1989; before that only scanned images of the original records exist. We show that text recognition followed by natural language processing can unlock this corpus for historical research. Using Transkribus, we trained a text recogniser (1.5% CER) that we applied to 3,156 images from 1946 and 1947. As low-quality recognition is inevitable, we trained a language model on the transcribed text and applied it to recognised text, discarding records with high average cross-entropy. Using information extraction techniques, we sampled speeches that were applauded and we introduce the first quantification of issues that were thus received. All our resources will be made public. Our model is publicly available through the Transkribus platform (http://www.transkribus.org/) under the name "Greek Parliamentary Proceedings 1946".