@inproceedings{caspani-etal-2020-acnlp,
title = "{ACNLP} at {S}em{E}val-2020 Task 6: A Supervised Approach for Definition Extraction",
author = "Caspani, Fabien and
Ratnamogan, Pirashanth and
Linger, Mathis and
Hajaiej, Mhamed",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.58/",
doi = "10.18653/v1/2020.semeval-1.58",
pages = "479--486",
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."
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<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.</abstract>
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%0 Conference Proceedings
%T ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction
%A Caspani, Fabien
%A Ratnamogan, Pirashanth
%A Linger, Mathis
%A Hajaiej, Mhamed
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F caspani-etal-2020-acnlp
%X 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.
%R 10.18653/v1/2020.semeval-1.58
%U https://aclanthology.org/2020.semeval-1.58/
%U https://doi.org/10.18653/v1/2020.semeval-1.58
%P 479-486
Markdown (Informal)
[ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction](https://aclanthology.org/2020.semeval-1.58/) (Caspani et al., SemEval 2020)
ACL