About Evaluation of F1 Score for RECENT Relation Extraction System
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Abstract (arXiv)
This document contains a discussion of the F1 score evaluation used in the article 'Relation Classification with Entity Type Restriction' by Shengfei Lyu, Huanhuan Chen published on Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. The authors created a system named RECENT and claim it achieves (then) a new state-of-the-art result 75.2 (previous 74.8) on the TACRED dataset, while after correcting errors and reevaluation the final result is 65.16
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 7 references that are in the map. First posted on arXiv 16 May 2023.
Builds on
6 of 7 references.
References · 6
- 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
- 2018Graph Convolution over Pruned Dependency Trees Improves Relation Extractioncited by 146
- 2021An Improved Baseline for Sentence-level Relation Extractioncited by 80
- 2021Relation Classification with Entity Type Restrictioncited by 31
- 2020Relation Classification as Two-way Span-Predictioncited by 9
- 2021Improving Sentence-Level Relation Extraction through Curriculum Learningcited by 8
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Citing papers per year: 2026: 1.
1 paper.