DSC IIT-ISM at SemEval-2020 Task 6: Boosting BERT with Dependencies for Definition Extraction
TL
TL;DR
This work explores the performance of Bidirectional Encoder Representations from Transformers at definition extraction and proposes a joint model of BERT and Text Level Graph Convolutional Network so as to incorporate dependencies into the model.
Abstract
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).
References21 items
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SemEval-2020 Task 6: Definition Extraction from Free Text with the DEFT Corpus
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An Explainable Machine Learning Approach for Definition Extraction
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A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency
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Text Level Graph Neural Network for Text Classification
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