Rahul Goel, Waleed Ammar, Aditya Gupta, Siddharth Vashishtha, Motoki Sano, Faiz Surani, Max Chang, HyunJeong Choe, David Greene, Chuan He, Rattima Nitisaroj, Anna Trukhina, Shachi Paul, Pararth Shah, Rushin Shah, Zhou Yu. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.

We propose a supervised method of extracting event causalities like conduct slash-and-burn agriculture→exacerbate desertification from the web using se-mantic relation (between nouns), context, and association features. Experiments show that our method outperforms base-lines that are based on state-of-the-art methods. We also propose methods of generating future scenarios like conduct slash-and-burn agriculture→exacerbate desertification→increase Asian dust (from China)→asthma gets worse. Experi-ments show that we can generate 50,000 scenarios with 68 % precision. We also generated a scenario deforestation con-tinues→global warming worsens→sea temperatures rise→vibrio parahaemolyti-cus fouls (water), which is written in no document in our input web corpus crawled in 2007. But the vibrio risk due to global warming was observed in Baker-Austin et al. (2013). Thus, we “predicted ” the future event sequence in a sense. 1

Julien Kloetzer, Stijn De Saeger, Kentaro Torisawa, Chikara Hashimoto, Jong-Hoon Oh, Motoki Sano, Kiyonori Ohtake. Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. 2013.