Abstract
Combinatory categorial grammars are linguistically motivated and useful for semantic parsing, but costly to acquire in a supervised way and difficult to acquire in an unsupervised way. We propose an alternative making use of cross-lingual learning: an existing source-language parser is used together with a parallel corpus to induce a grammar and parsing model for a target language. On the PASCAL benchmark, cross-lingual CCG induction outperforms CCG induction from gold-standard POS tags on 3 out of 8 languages, and unsupervised CCG induction on 6 out of 8 languages. We also show that cross-lingually induced CCGs reflect syntactic properties of the target languages.- Anthology ID:
- N19-1160
- Volume:
- Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1577–1587
- Language:
- URL:
- https://aclanthology.org/N19-1160
- DOI:
- 10.18653/v1/N19-1160
- Cite (ACL):
- Kilian Evang. 2019. Cross-lingual CCG Induction. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 1577–1587, Minneapolis, Minnesota. Association for Computational Linguistics.
- Cite (Informal):
- Cross-lingual CCG Induction (Evang, NAACL 2019)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/N19-1160.pdf
- Code
- texttheater/xlci