# DSC IIT-ISM at SemEval-2020 Task 6: Boosting BERT with Dependencies for Definition Extraction

arXiv: https://arxiv.org/abs/2009.08180 · HTML: https://mlsanity.com/paper/2009.08180/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Sep 2020.

## Built on by (most cited first, 2 of 2)

- [SciDr at SDU-2020: IDEAS -- Identifying and Disambiguating Everyday Acronyms for Scientific Domain](https://mlsanity.com/paper/2102.08818/) (2021)
- [Fine-Tuning BERTs for Definition Extraction from Mathematical Text](https://mlsanity.com/paper/2406.13827/) (2024)

## Abstract (arXiv)

We explore the performance of Bidirectional Encoder Representations from Transformers (BERT) at definition extraction. We further propose a joint model of BERT and Text Level Graph Convolutional Network so as to incorporate dependencies into the model. Our proposed model produces better results than BERT and achieves comparable results to BERT with fine tuned language model in DeftEval (Task 6 of SemEval 2020), a shared task of classifying whether a sentence contains a definition or not (Subtask 1).