Automatic Term Name Generation for Gene Ontology: Task and Dataset
Yanjian Zhang, Qin Chen, Yiteng Zhang, Zhongyu Wei, Yixu Gao, Jiajie Peng, Zengfeng Huang, Weijian Sun, Xuanjing Huang
Abstract
Terms contained in Gene Ontology (GO) have been widely used in biology and bio-medicine. Most previous research focuses on inferring new GO terms, while the term names that reflect the gene function are still named by the experts. To fill this gap, we propose a novel task, namely term name generation for GO, and build a large-scale benchmark dataset. Furthermore, we present a graph-based generative model that incorporates the relations between genes, words and terms for term name generation, which exhibits great advantages over the strong baselines.- Anthology ID:
- 2020.findings-emnlp.422
- Original:
- 2020.findings-emnlp.422v1
- Version 2:
- 2020.findings-emnlp.422v2
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4705–4710
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.422
- DOI:
- 10.18653/v1/2020.findings-emnlp.422
- Cite (ACL):
- Yanjian Zhang, Qin Chen, Yiteng Zhang, Zhongyu Wei, Yixu Gao, Jiajie Peng, Zengfeng Huang, Weijian Sun, and Xuanjing Huang. 2020. Automatic Term Name Generation for Gene Ontology: Task and Dataset. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4705–4710, Online. Association for Computational Linguistics.
- Cite (Informal):
- Automatic Term Name Generation for Gene Ontology: Task and Dataset (Zhang et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2020.findings-emnlp.422.pdf