Counts@IITK at SemEval-2021 Task 8: SciBERT Based Entity And Semantic Relation Extraction For Scientific Data
This paper presents the system for SemEval 2021 Task 8 (MeasEval). MeasEval is a novel span extraction, classification, and relation extraction task focused on finding quantities, attributes of these quantities, and additional information, including the related measured entities, properties, and measurement contexts. Our submitted system, which placed fifth (team rank) on the leaderboard, consisted of SciBERT with [CLS] token embedding and CRF layer on top. We were also placed first in Quantity (tied) and Unit subtasks, second in MeasuredEntity, Modifier and Qualifies subtasks, and third in Qualifier subtask.
Code (1)
Tasks
Relation ExtractionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
KnowGraph@IITK at SemEval-2021 Task 11: Building KnowledgeGraph for NLP Research
Research in Natural Language Processing is making rapid advances, resulting in the publication of a large number of research papers. Finding relevant research papers and their contribution to the domain is a challenging …
TripletKnowGraph@IITK at SemEval-2021 Task 11: Building Knowledge Graph for NLP Research
Research in Natural Language Processing is making rapid advances, resulting in the publication of a large number of research papers. Finding relevant research papers and their contribution to the domain is a challenging …
TripletJBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their Descriptions
This paper describes our system in the SemEval-2022 Task 12: ‘linking mathematical symbols to their descriptions’, achieving first on the leaderboard for all the subtasks comprising named entity extraction (NER) and rela…
Joint Entity and Relation ExtractionMachine Reading ComprehensionNERReading Comprehension+1IITK at SemEval-2020 Task 10: Transformers for Emphasis Selection
This paper describes the system proposed for addressing the research problem posed in Task 10 of SemEval-2020: Emphasis Selection For Written Text in Visual Media. We propose an end-to-end model that takes as input the t…
IITK@LCP at SemEval 2021 Task 1: Classification for Lexical Complexity Regression Task
This paper describes our contribution to SemEval 2021 Task 1: Lexical Complexity Prediction. In our approach, we leverage the ELECTRA model and attempt to mirror the data annotation scheme. Although the task is a regress…
General ClassificationLexical Complexity PredictionregressionTask 2