GALLOC: a GeoAnnotator for Labeling LOCation descriptions from disaster-related text messages

During a natural disaster, people post text messages on various platforms, such as social media and short message service (SMS) platforms, to share urgent information and seek help. Many text messages contain location descriptions about victims and accidents. Accurately extracting these location descriptions can help disaster responders reach victims more quickly and even save lives. These location descriptions, however, are often more complex than simple place names (e.g. city names), and cannot be extracted using typical named entity recognition approaches. While new machine learning models could be trained, they require labeled training data that are time-consuming to create without an effective data annotation tool. To fill this gap, we develop GALLOC, a GeoAnnotator for Labeling LOCation descriptions from disaster-related text messages. GALLOC is an open-source and Web-based tool that provides a variety of functions for supporting location description annotation, such as artificial intelligence powered pre-annotation and automatic spatial footprint identification. It also supports multilingual data annotation, and can be used by a group of users to collaboratively create a dataset. We present the design considerations and functions of GALLOC and evaluate it via a comparison with previous tools and an experiment to annotate a small set of disaster-related messages.