ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction

Fabien Caspani, Pirashanth Ratnamogan, Mathis Linger, Mhamed Hajaiej


Abstract
We describe our contribution to two of the subtasks of SemEval 2020 Task 6, DeftEval: Extracting term-definition pairs in free text. The system for Subtask 1: Sentence Classification is based on a transformer architecture where we use transfer learning to fine-tune a pretrained model on the downstream task, and the one for Subtask 3: Relation Classification uses a Random Forest classifier with handcrafted dedicated features. Our systems respectively achieve 0.830 and 0.994 F1-scores on the official test set, and we believe that the insights derived from our study are potentially relevant to help advance the research on definition extraction.
Anthology ID:
2020.semeval-1.58
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
479–486
Language:
URL:
https://aclanthology.org/2020.semeval-1.58
DOI:
10.18653/v1/2020.semeval-1.58
Bibkey:
Cite (ACL):
Fabien Caspani, Pirashanth Ratnamogan, Mathis Linger, and Mhamed Hajaiej. 2020. ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 479–486, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction (Caspani et al., SemEval 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp-22-attachments/2020.semeval-1.58.pdf
Data
DEFT Corpus