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 extract phrases from each sentence and format into 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.
|Original language||English (US)|
|Title of host publication||SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop|
|Editors||Alexis Palmer, Nathan Schneider, Natalie Schluter, Guy Emerson, Aurelie Herbelot, Xiaodan Zhu|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||12|
|State||Published - 2021|
|Event||15th International Workshop on Semantic Evaluation, SemEval 2021 - Virtual, Bangkok, Thailand|
Duration: Aug 5 2021 → Aug 6 2021
|Name||SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop|
|Conference||15th International Workshop on Semantic Evaluation, SemEval 2021|
|Period||8/5/21 → 8/6/21|
Bibliographical notePublisher Copyright:
© 2021 Association for Computational Linguistics.