Abstract
The task of Fine-grained Entity Type Classification (FETC) consists of assigning types from a hierarchy to entity mentions in text. Existing methods rely on distant supervision and are thus susceptible to noisy labels that can be out-of-context or overly-specific for the training sentence. Previous methods that attempt to address these issues do so with heuristics or with the help of hand-crafted features. Instead, we propose an end-to-end solution with a neural network model that uses a variant of cross-entropy loss function to handle out-of-context labels, and hierarchical loss normalization to cope with overly-specific ones. Also, previous work solve FETC a multi-label classification followed by ad-hoc post-processing. In contrast, our solution is more elegant: we use public word embeddings to train a single-label that jointly learns representations for entity mentions and their context. We show experimentally that our approach is robust against noise and consistently outperforms the state-of-the-art on established benchmarks for the task.- Anthology ID:
- N18-1002
- Volume:
- Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 16–25
- Language:
- URL:
- https://aclanthology.org/N18-1002
- DOI:
- 10.18653/v1/N18-1002
- Cite (ACL):
- Peng Xu and Denilson Barbosa. 2018. Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 16–25, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss (Xu & Barbosa, NAACL 2018)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/N18-1002.pdf
- Code
- billy-inn/NFETC + additional community code
- Data
- FIGER