Predicting future international events from textual information, such as news articles, has tremendous potential for applications in global policy, strategic decision-making, and geopolitics. However, existing datasets available for this task are often limited in quality, hindering the progress of related research. In this paper, we introduce WORLDREP (WORLD Relationship and Event Prediction), a novel dataset designed to address these limitations by leveraging the advanced reasoning capabilities of large-language models (LLMs). Our dataset features high-quality scoring labels generated through advanced prompt modeling and rigorously validated by domain experts in political science. We showcase the quality and utility of WORLDREP for real-world event prediction tasks, demonstrating its effectiveness through extensive experiments and analysis. Furthermore, we publicly release our dataset along with the full automation source code for data collection, labeling, and benchmarking, aiming to support and advance research in text-based event prediction.

In our daily lives, as in science and in all other domains, we encounter huge numbers of dispositions (tendencies, potentials, powers) which are realized in processes such as sneezing, sweating, shedding dandruff, and on and on. Among this plethora of what we can think of as mere dispositions is a subset of dispositions in whose realizations we have an interest a car responding well when driven on ice, a rabbits lungs responding well when it is chased by a wolf, and so on. We call the latter capabilities and we attempt to provide a robust ontological account of what capabilities are that is of sufficient generality to serve a variety of purposes, for example by providing a useful extension to ontology-based research in areas where capabilities data are currently being collected in siloed fashion.

Israeli forces have hit a tent in Rafah housing displaced Palestinians, killing at least 11 people, according to local authorities, hours after 17 people were killed in attacks elsewhere in the Gaza Strip. At least 50 people were injured in Saturday's drone attack, which took place next to the entrance of the Al-Helal Al-Emirati Maternity Hospital in Tal as-Sultan, Rafah City, Gaza's Ministry of Health said in a statement. The ministry said Abdel Fattah Abu Marhi, the head of the paramedic unit at the hospital, was killed, and that children were among the injured. "A tent filled with displaced evacuees in the area, including an entire family, has been directly hit by a drone strike," said Al Jazeera's Hani Mahmoud, reporting from Rafah. He said eight of the bodies had been taken to the Kuwait Hospital "where the scene is very chaotic" as the small facility is unprepared for the large number of injuries arriving there.

An Israeli drone strike has targeted two journalists in Muraj, north of Rafah, including Al Jazeera Arabic correspondent, Ismail Abu Omar who doctors say is in a critical condition.

Almost ten years after Google secretly started work on technology that would allow a vehicle to operate without a human driver, the company has launched the nation's first commercial self-driving robo-taxi. Waymo, a subsidiary of Google, introduced a small fleet of ride-hailing vehicles in Phoenix, Arizona, asking people to pay, just as they would to travel by Uber or Lyft. For now, the project will also feature a human driver behind the wheel, just in case the robotic vehicle malfunctions. "Over time, we hope to make Waymo One available to even more members of the public Self-driving technology is new to many, so we're proceeding carefully," Waymo's CEO John Krafcik, wrote in a blog post about Wednesday's run-out. He added: "Almost 10 years ago, we were founded as the Google self-driving car project to explore one simple question: how can we best use fully self-driving technology to make roads safer? We've been focused on building the world's most experienced driver ever since."

Virtual assistants such as Amazon's Alexa and Google Home have the capacity to analyse how happy and healthy a couple's relationship is, research has found. In-home listening devices will soon be able to judge how functional relationships are as well as interrupt an argument with an idea for how to resolve it, the study said. The research, by Imperial College Business School, stated that within the next two to three years, digital assistants could predict with 75 per cent accuracy the likelihood of a relationship or marriage being a success. The technology would reach a verdict through acoustic analysis of communication between couples – examining everything from everyday encounters to arguments. The virtual assistants would then be able to provide relationship advice and what researchers refer to as democratising counselling.