A Joint Named-Entity Recognizer for Heterogeneous Tag-sets Using a Tag Hierarchy
Genady Beryozkin, Yoel Drori, Oren Gilon, Tzvika Hartman, Idan Szpektor
Abstract
We study a variant of domain adaptation for named-entity recognition where multiple, heterogeneously tagged training sets are available. Furthermore, the test tag-set is not identical to any individual training tag-set. Yet, the relations between all tags are provided in a tag hierarchy, covering the test tags as a combination of training tags. This setting occurs when various datasets are created using different annotation schemes. This is also the case of extending a tag-set with a new tag by annotating only the new tag in a new dataset. We propose to use the given tag hierarchy to jointly learn a neural network that shares its tagging layer among all tag-sets. We compare this model to combining independent models and to a model based on the multitasking approach. Our experiments show the benefit of the tag-hierarchy model, especially when facing non-trivial consolidation of tag-sets.- Anthology ID:
- P19-1014
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 140–150
- Language:
- URL:
- https://aclanthology.org/P19-1014
- DOI:
- 10.18653/v1/P19-1014
- Cite (ACL):
- Genady Beryozkin, Yoel Drori, Oren Gilon, Tzvika Hartman, and Idan Szpektor. 2019. A Joint Named-Entity Recognizer for Heterogeneous Tag-sets Using a Tag Hierarchy. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 140–150, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- A Joint Named-Entity Recognizer for Heterogeneous Tag-sets Using a Tag Hierarchy (Beryozkin et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/P19-1014.pdf