Abstract
隐喻是人类思维和语言理解的核心问题。随着互联网发展和海量文本出现,利用自然语言处理技术对隐喻文本进行自动识别成为一种迫切的需求。但是目前在汉语隐喻识别研究中,由于语义资源有限,导致模型容易过拟合。此外,主流隐喻识别方法存在可解释性差的缺点。针对上述问题,本文构建了一个规模较大的汉语动词隐喻数据集,并且提出了一种基于HowNet的无监督汉语动词隐喻识别模型。实验结果表明,本文提出的模型能够有效地应用于动词隐喻识别任务,识别效果超过了对比的无监督模型;并且,与其它用于隐喻识别的深度学习模型相比,本文模型具有结构简单、参数少、可解释性强的优点。- Anthology ID:
- 2021.ccl-1.25
- Volume:
- Proceedings of the 20th Chinese National Conference on Computational Linguistics
- Month:
- August
- Year:
- 2021
- Address:
- Huhhot, China
- Editors:
- Sheng Li (李生), Maosong Sun (孙茂松), Yang Liu (刘洋), Hua Wu (吴华), Kang Liu (刘康), Wanxiang Che (车万翔), Shizhu He (何世柱), Gaoqi Rao (饶高琦)
- Venue:
- CCL
- SIG:
- Publisher:
- Chinese Information Processing Society of China
- Note:
- Pages:
- 258–268
- Language:
- Chinese
- URL:
- https://aclanthology.org/2021.ccl-1.25
- DOI:
- Cite (ACL):
- Minghao Zhang, Dongyu Zhang, and Hongfei Lin. 2021. 基于HowNet的无监督汉语动词隐喻识别方法(Unsupervised Chinese Verb Metaphor Recognition Method Based on HowNet). In Proceedings of the 20th Chinese National Conference on Computational Linguistics, pages 258–268, Huhhot, China. Chinese Information Processing Society of China.
- Cite (Informal):
- 基于HowNet的无监督汉语动词隐喻识别方法(Unsupervised Chinese Verb Metaphor Recognition Method Based on HowNet) (Zhang et al., CCL 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2021.ccl-1.25.pdf