| Autor: |
Xiangyang Mou, Chenghao Yang, Mo Yu, Bingsheng Yao, Xiaoxiao Guo, Saloni Potdar, Hui Su |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Transactions of the Association for Computational Linguistics, Vol 9, Pp 1032-1046 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2307-387X |
| DOI: |
10.1162/tacl_a_00411/107386/Narrative-Question-Answering-with-Cutting-Edge |
| Popis: |
AbstractRecent advancements in open-domain question answering (ODQA), that is, finding answers from large open-domain corpus like Wikipedia, have led to human-level performance on many datasets. However, progress in QA over book stories (Book QA) lags despite its similar task formulation to ODQA. This work provides a comprehensive and quantitative analysis about the difficulty of Book QA: (1) We benchmark the research on the NarrativeQA dataset with extensive experiments with cutting-edge ODQA techniques. This quantifies the challenges Book QA poses, as well as advances the published state-of-the-art with a ∼7% absolute improvement on ROUGE-L. (2) We further analyze the detailed challenges in Book QA through human studies.1 Our findings indicate that the event-centric questions dominate this task, which exemplifies the inability of existing QA models to handle event-oriented scenarios. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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