Abstract
As a fundamental natural language processing task and one of core knowledge extraction techniques, named entity recognition (NER) is widely used to extract information from texts for downstream tasks. Nested NER is a branch of NER in which the named entities (NEs) are nested with each other. However, most of the previous studies on nested NER usually apply linear structure to model the nested NEs which are actually accommodated in a hierarchical structure. Thus in order to address this mismatch, this work models the full nested NEs in a sentence as a holistic structure, then we propose a holistic structure parsing algorithm to disclose the entire NEs once for all. Besides, there is no research on applying corpus-level information to NER currently. To make up for the loss of this information, we introduce Point-wise Mutual Information (PMI) and other frequency features from corpus-aware statistics for even better performance by holistic modeling from sentence-level to corpus-level. Experiments show that our model yields promising results on widely-used benchmarks which approach or even achieve state-of-the-art. Further empirical studies show that our proposed corpus-aware features can substantially improve NER domain adaptation, which demonstrates the surprising advantage of our proposed corpus-level holistic structure modeling.- Anthology ID:
- 2022.coling-1.218
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 2472–2482
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.218
- DOI:
- Cite (ACL):
- Yifei Yang, Zuchao Li, and Hai Zhao. 2022. Nested Named Entity Recognition as Corpus Aware Holistic Structure Parsing. In Proceedings of the 29th International Conference on Computational Linguistics, pages 2472–2482, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Nested Named Entity Recognition as Corpus Aware Holistic Structure Parsing (Yang et al., COLING 2022)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2022.coling-1.218.pdf
- Data
- GENIA