Abstract
It can be challenging to build effective open question answering (open QA) systems for languages other than English, mainly due to a lack of labeled data for training. We present a data efficient method to bootstrap such a system for languages other than English. Our approach requires only limited QA resources in the given language, along with machine-translated data, and at least a bilingual language model. To evaluate our approach, we build such a system for the Icelandic language and evaluate performance over trivia style datasets. The corpora used for training are English in origin but machine translated into Icelandic. We train a bilingual Icelandic/English language model to embed English context and Icelandic questions following methodology introduced with DensePhrases (Lee et al., 2021). The resulting system is an open domain cross-lingual QA system between Icelandic and English. Finally, the system is adapted for Icelandic only open QA, demonstrating how it is possible to efficiently create an open QA system with limited access to curated datasets in the language of interest.- Anthology ID:
- 2022.mia-1.4
- Volume:
- Proceedings of the Workshop on Multilingual Information Access (MIA)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, USA
- Editors:
- Akari Asai, Eunsol Choi, Jonathan H. Clark, Junjie Hu, Chia-Hsuan Lee, Jungo Kasai, Shayne Longpre, Ikuya Yamada, Rui Zhang
- Venue:
- MIA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 29–36
- Language:
- URL:
- https://aclanthology.org/2022.mia-1.4
- DOI:
- 10.18653/v1/2022.mia-1.4
- Cite (ACL):
- Vésteinn Snæbjarnarson and Hafsteinn Einarsson. 2022. Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic. In Proceedings of the Workshop on Multilingual Information Access (MIA), pages 29–36, Seattle, USA. Association for Computational Linguistics.
- Cite (Informal):
- Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic (Snæbjarnarson & Einarsson, MIA 2022)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/2022.mia-1.4.pdf
- Data
- NQiI, Natural Questions, NewsQA