Abstract
This paper describes our system in the SemEval-2022 Task 12: ‘linking mathematical symbols to their descriptions’, achieving first on the leaderboard for all the subtasks comprising named entity extraction (NER) and relation extraction (RE). Our system is a two-stage pipeline model based on SciBERT that detects symbols, descriptions, and their relationships in scientific documents. The system consists of 1) machine reading comprehension(MRC)-based NER model, where each entity type is represented as a question and its entity mention span is extracted as an answer using an MRC model, and 2) span pair classification for RE, where two entity mentions and their type markers are encoded into span representations that are then fed to a Softmax classifier. In addition, we deploy a rule-based symbol tokenizer to improve the detection of the exact boundary of symbol entities. Regularization and ensemble methods are further explored to improve the RE model.- Anthology ID:
- 2022.semeval-1.231
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1679–1686
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.231
- DOI:
- 10.18653/v1/2022.semeval-1.231
- Cite (ACL):
- Sung-Min Lee and Seung-Hoon Na. 2022. JBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their Descriptions. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1679–1686, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- JBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their Descriptions (Lee & Na, SemEval 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.semeval-1.231.pdf
- Code
- zizun/symlink
- Data
- SemEval-2022 Task-12