{"main_file_link":[{"url":"https://aclanthology.org/2022.coling-1.291.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"publication":"Proceedings of the 29th International Conference on Computational Linguistics","type":"conference","date_updated":"2023-07-02T18:14:01Z","page":"3296–3308","oa":"1","author":[{"first_name":"Alexander","full_name":"Bondarenko, Alexander","last_name":"Bondarenko"},{"first_name":"Magdalena","last_name":"Wolska","full_name":"Wolska, Magdalena"},{"orcid":"0000-0002-4525-6865","first_name":"Stefan","id":"11871","last_name":"Heindorf","full_name":"Heindorf, Stefan"},{"full_name":"Blübaum, Lukas","last_name":"Blübaum","first_name":"Lukas"},{"first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"},{"last_name":"Stein","full_name":"Stein, Benno","first_name":"Benno"},{"first_name":"Pavel","full_name":"Braslavski, Pavel","last_name":"Braslavski"},{"last_name":"Hagen","full_name":"Hagen, Matthias","first_name":"Matthias"},{"full_name":"Potthast, Martin","last_name":"Potthast","first_name":"Martin"}],"abstract":[{"lang":"eng","text":"At least 5% of questions submitted to search engines ask about cause-effect relationships in some way. To support the development of tailored approaches that can answer such questions, we construct Webis-CausalQA-22, a benchmark corpus of 1.1 million causal questions with answers. We distinguish different types of causal questions using a novel typology derived from a data-driven, manual analysis of questions from ten large question answering (QA) datasets. Using high-precision lexical rules, we extract causal questions of each type from these datasets to create our corpus. As an initial baseline, the state-of-the-art QA model UnifiedQA achieves a ROUGE-L F1 score of 0.48 on our new benchmark."}],"publisher":"International Committee on Computational Linguistics","place":"Gyeongju, Republic of Korea","year":"2022","project":[{"_id":"52","name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"status":"public","date_created":"2022-10-15T19:33:10Z","citation":{"short":"A. Bondarenko, M. Wolska, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, B. Stein, P. Braslavski, M. Hagen, M. Potthast, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 3296–3308.","chicago":"Bondarenko, Alexander, Magdalena Wolska, Stefan Heindorf, Lukas Blübaum, Axel-Cyrille Ngonga Ngomo, Benno Stein, Pavel Braslavski, Matthias Hagen, and Martin Potthast. “CausalQA: A Benchmark for Causal Question Answering.” In <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 3296–3308. Gyeongju, Republic of Korea: International Committee on Computational Linguistics, 2022.","bibtex":"@inproceedings{Bondarenko_Wolska_Heindorf_Blübaum_Ngonga Ngomo_Stein_Braslavski_Hagen_Potthast_2022, place={Gyeongju, Republic of Korea}, title={CausalQA: A Benchmark for Causal Question Answering}, booktitle={Proceedings of the 29th International Conference on Computational Linguistics}, publisher={International Committee on Computational Linguistics}, author={Bondarenko, Alexander and Wolska, Magdalena and Heindorf, Stefan and Blübaum, Lukas and Ngonga Ngomo, Axel-Cyrille and Stein, Benno and Braslavski, Pavel and Hagen, Matthias and Potthast, Martin}, year={2022}, pages={3296–3308} }","apa":"Bondarenko, A., Wolska, M., Heindorf, S., Blübaum, L., Ngonga Ngomo, A.-C., Stein, B., Braslavski, P., Hagen, M., &#38; Potthast, M. (2022). CausalQA: A Benchmark for Causal Question Answering. <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 3296–3308.","ama":"Bondarenko A, Wolska M, Heindorf S, et al. CausalQA: A Benchmark for Causal Question Answering. In: <i>Proceedings of the 29th International Conference on Computational Linguistics</i>. International Committee on Computational Linguistics; 2022:3296–3308.","mla":"Bondarenko, Alexander, et al. “CausalQA: A Benchmark for Causal Question Answering.” <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, International Committee on Computational Linguistics, 2022, pp. 3296–3308.","ieee":"A. Bondarenko <i>et al.</i>, “CausalQA: A Benchmark for Causal Question Answering,” in <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 2022, pp. 3296–3308."},"user_id":"11871","department":[{"_id":"574"},{"_id":"760"}],"title":"CausalQA: A Benchmark for Causal Question Answering","_id":"33739"}