@inproceedings{martin-pedersen-2021-duluth,
title = "{D}uluth at {S}em{E}val-2021 Task 11: Applying {D}e{BERT}a to Contributing Sentence Selection and Dependency Parsing for Entity Extraction",
author = "Martin, Anna and
Pedersen, Ted",
editor = "Palmer, Alexis and
Schneider, Nathan and
Schluter, Natalie and
Emerson, Guy and
Herbelot, Aurelie and
Zhu, Xiaodan",
booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.semeval-1.60",
doi = "10.18653/v1/2021.semeval-1.60",
pages = "490--501",
abstract = "This paper describes the Duluth system that participated in SemEval-2021 Task 11, NLP Contribution Graph. It details the extraction of contribution sentences and scientific entities and their relations from scholarly articles in the domain of Natural Language Processing. Our solution uses deBERTa for multi-class sentence classification to extract the contributing sentences and their type, and dependency parsing to outline each sentence and extract subject-predicate-object triples. Our system ranked fifth of seven for Phase 1: end-to-end pipeline, sixth of eight for Phase 2 Part 1: phrases and triples, and fifth of eight for Phase 2 Part 2: triples extraction.",
}
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<abstract>This paper describes the Duluth system that participated in SemEval-2021 Task 11, NLP Contribution Graph. It details the extraction of contribution sentences and scientific entities and their relations from scholarly articles in the domain of Natural Language Processing. Our solution uses deBERTa for multi-class sentence classification to extract the contributing sentences and their type, and dependency parsing to outline each sentence and extract subject-predicate-object triples. Our system ranked fifth of seven for Phase 1: end-to-end pipeline, sixth of eight for Phase 2 Part 1: phrases and triples, and fifth of eight for Phase 2 Part 2: triples extraction.</abstract>
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%0 Conference Proceedings
%T Duluth at SemEval-2021 Task 11: Applying DeBERTa to Contributing Sentence Selection and Dependency Parsing for Entity Extraction
%A Martin, Anna
%A Pedersen, Ted
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Schluter, Natalie
%Y Emerson, Guy
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%S Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F martin-pedersen-2021-duluth
%X This paper describes the Duluth system that participated in SemEval-2021 Task 11, NLP Contribution Graph. It details the extraction of contribution sentences and scientific entities and their relations from scholarly articles in the domain of Natural Language Processing. Our solution uses deBERTa for multi-class sentence classification to extract the contributing sentences and their type, and dependency parsing to outline each sentence and extract subject-predicate-object triples. Our system ranked fifth of seven for Phase 1: end-to-end pipeline, sixth of eight for Phase 2 Part 1: phrases and triples, and fifth of eight for Phase 2 Part 2: triples extraction.
%R 10.18653/v1/2021.semeval-1.60
%U https://aclanthology.org/2021.semeval-1.60
%U https://doi.org/10.18653/v1/2021.semeval-1.60
%P 490-501
Markdown (Informal)
[Duluth at SemEval-2021 Task 11: Applying DeBERTa to Contributing Sentence Selection and Dependency Parsing for Entity Extraction](https://aclanthology.org/2021.semeval-1.60) (Martin & Pedersen, SemEval 2021)
ACL