X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
Mostafa Abdou, Cezar Sas, Rahul Aralikatte, Isabelle Augenstein, Anders Søgaard
Abstract
Although the vast majority of knowledge bases (KBs) are heavily biased towards English, Wikipedias do cover very different topics in different languages. Exploiting this, we introduce a new multilingual dataset (X-WikiRE), framing relation extraction as a multilingual machine reading problem. We show that by leveraging this resource it is possible to robustly transfer models cross-lingually and that multilingual support significantly improves (zero-shot) relation extraction, enabling the population of low-resourced KBs from their well-populated counterparts.- Anthology ID:
- D19-6130
- Volume:
- Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Colin Cherry, Greg Durrett, George Foster, Reza Haffari, Shahram Khadivi, Nanyun Peng, Xiang Ren, Swabha Swayamdipta
- Venue:
- WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 265–274
- Language:
- URL:
- https://aclanthology.org/D19-6130
- DOI:
- 10.18653/v1/D19-6130
- Cite (ACL):
- Mostafa Abdou, Cezar Sas, Rahul Aralikatte, Isabelle Augenstein, and Anders Søgaard. 2019. X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension. In Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), pages 265–274, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension (Abdou et al., 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/D19-6130.pdf
- Code
- mhany90/Multi-WikiRE
- Data
- X-WikiRE