  The importance of social media is again exposed in the recent tragedy of the
2023 Turkey and Syria earthquake. Many victims who were trapped under the
rubble called for help by posting messages in Twitter. We present an
interactive tool to provide situational awareness for missing and trapped
people, and disaster relief for rescue and donation efforts. The system (i)
collects tweets, (ii) classifies the ones calling for help, (iii) extracts
important entity tags, and (iv) visualizes them in an interactive map screen.
Our initial experiments show that the performance in terms of the F1 score is
up to 98.30 for tweet classification, and 84.32 for entity extraction. The
demonstration, dataset, and other related files can be accessed at
https://github.com/avaapm/deprem
