BERTatDE at SemEval-2020 Task 6: Extracting Term-definition Pairs in Free Text Using Pre-trained Model
Huihui
Zhang
author
Feiliang
Ren
author
2020-12
text
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Aurelie
Herbelot
editor
Xiaodan
Zhu
editor
Alexis
Palmer
editor
Nathan
Schneider
editor
Jonathan
May
editor
Ekaterina
Shutova
editor
International Committee for Computational Linguistics
Barcelona (online)
conference publication
Definition extraction is an important task in Nature Language Processing, and it is used to identify the terms and definitions related to terms. The task contains sentence classification task (i.e., classify whether it contains definition) and sequence labeling task (i.e., find the boundary of terms and definitions). The paper describes our system BERTatDE1 in sentence classification task (subtask 1) and sequence labeling task (subtask 2) in the definition extraction (SemEval-2020 Task 6). We use BERT to solve the multi-domain problems including the uncertainty of term boundary that is, different areas have different ways to definite the domain related terms. We use BERT, BiLSTM and attention in subtask 1 and our best result achieved 79.71% in F1 and the eighteenth place in subtask 1. For the subtask 2, we use BERT, BiLSTM and CRF to sequence labeling, and achieve 40.73% in Macro-averaged F1.
zhang-ren-2020-bertatde
10.18653/v1/2020.semeval-1.90
https://aclanthology.org/2020.semeval-1.90
2020-12
690
696